Green Roof Modules Research Articles

More than sedum: Colonizing weedy species can provide equivalent green roof ecosystem services

Green roofs are typically constructed for their provision of both environmental and associated economic benefits including increased habitat, thermal regulation, mitigation of air and noise pollution, and stormwater retention. The provision of these various ecosystem services is sharply influenced by plant species composition, with particular species and traits known to excel at specific services. For this reason, increased biodiversity can improve the overall provision of ecosystem services. However, one key contributor to green roof biodiversity, colonizing species, is understudied. In this study we examine the contribution of common colonizing species (lawn weeds) and one green roof species, to three important ecosystem services: stormwater retention, temperature reduction, and nitrogen retention. This experiment used replicated green roof modules to examine 13 different treatments: eight colonizing species in monoculture, one green roof species monoculture, two treatments with a mix of colonizing species, one treatment where vegetation was allowed to spontaneously colonize, and one substrate only control. Results from this study show that mixtures of colonizing species performed well for all three monitored ecosystem services, with a few of the monocultures, especially those with high biomass or canopy density, performing similarly. While it is unlikely that green roof installations would proceed equally well without adding vegetation, our results indicate that colonizing species can support a viable green roof ecosystem. This study shows that spontaneous growth and/or allowing new species to colonize may be a viable design alternative for green roofs, decreasing cost while maintaining the desired ecosystem services.

Substrate moisture variations of extensive green roofs with different structural configurations in a semi-arid region: Observational data and dynamic simulation

Substrate moisture condition is crucial for hydrological performance, water management and plant survival of green roofs. To date, the behaviour of long-term substrate moisture of green roofs in various climate regions has not been well understood. In this study, 24 months continuous field monitoring of substrate moisture content within nine extensive green roof modules with varies structural configurations was conducted to investigate the impacts of structural configurations and meteorological factors on substrate moisture content, and identify the key parameters for simulating the long-term substrate moisture dynamics. Results showed that green roofs planted with SedumSpectabilehave the highest mean volumetricwater content (VWC) (0.12–0.15 m3/m3) compared to other plant species considered. Green roofs with 5-cm substrate depth had lower mean VWC (0.07–0.08 m3/m3) than other substrate depths. The average substrate moisture loss rate of green roofs in summer and autumn seasons was 1.35 and 1.22 mm/day, respectively, which was higher than the spring (0.73 mm/day) and winter (0.64 mm/day) seasons for 2021. There were significant differences in mean VWC of green roofs among substrate material types. The mean VWC of green roofs was gradually enhanced from 0.12 to 0.14 m3/m3 as the substrate depth increased from 5 cm to 15 cm. The differences of mean VWC among vegetation types were all extremely significant (p < 0.001). The relative humidity was the most significant influencing factor on the average VWC level (correlation coefficient r = 0.42), with antecedent dry weather period (ADWP) had less significant effects on substrate VWC (r = 0.33), and followed by precipitation depth (r = 0.27). However, there was no significant relationship between air temperature and average VWC level of green roofs as well as total solar radiation. Nash-Sutcliffe efficient (NSE) values of the model simulations ranged from 0.70 to 0.81, and the mean absolute relative error (MAE) values ranged from 1.25 to 2.36, which indicated the model can adequately simulate the long-term substrate moisture content dynamics of green roofs. The crop coefficient and maximum water holding capacity of the substrate were the key parameters affecting long-term moisture content simulation of green roofs. These results could provide scientific suggestions for selecting suitable structural configuration to enhance water holding capacity of extensive green roofs in arid climates.

Evaluating the effectiveness of spontaneous vegetation for stormwater mitigation on green roofs

Green roofs can reduce stormwater runoff in urban areas by capturing rainfall. The extent of this capture is partially influenced by vegetation type and cover, which can be manipulated to optimise run-off reduction. However, in the absence of routine maintenance, planted green roof vegetation is often replaced by ‘weedy’ spontaneous species with unknown rainfall retention qualities. To better understand the role of spontaneous vegetation in green roof stormwater mitigation, we undertook a 100-day rainfall simulation involving 14 plant species that occur spontaneously on green roofs in Mediterranean-type climates. Green roof modules were filled with either 7 cm (shallow) or 14 cm (deep) substrate. The substrate was either left bare or sown with the spontaneous species community, which established approximately 100 % cover prior to the beginning of the rainfall simulation. During the simulation, modules were subjected to a “dry” and then a “wet” rainfall phase, each based on historical climate records from Melbourne, Australia. The “dry” treatment replicated the timing and depth of the driest rainfall period on record, while the “wet” treatment applied rainfall depths randomly selected from the 90th, 95th, and 99th percentiles of recorded rainfall. Rainfall retention, evapotranspiration, time to initiation of runoff and soil water content was measured for 17 rainfall events. Spontaneous vegetation cover and both species and functional diversity were measured at the end of each rainfall phase, and biomass was measured at the end of the wet phase. During the dry phase, modules with spontaneous vegetation cover retained 88 % of applied rainfall regardless of substrate depth and had 6 % greater retention than bare substrate. During the wet phase, deep substrate modules with spontaneous vegetation cover had 30 % greater retention than other treatment combinations. At the end of the wet phase, spontaneous vegetation in deep substrate had 42 % greater biomass, 19 % greater coverage and more than twofold greater functional richness than in shallow substrate. These findings demonstrate that spontaneous vegetation can increase stormwater retention on green roofs relative to bare substrate and have similar retention performance to commonly utilised species. However, the extent to which stormwater mitigation on green roofs is enhanced by spontaneous vegetation is dependent on factors that are more important for rainfall retention, such as substrate depth and rainfall patterns.

Influence of green roof plant density and redirecting rainfall via runoff zones on rainfall retention and plant drought stress

Green roofs are a promising engineered ecosystem designed to reduce stormwater runoff and restore vegetation cover in cities. Plants can contribute to rainfall retention by rapidly depleting water in the substrate, however, this increases the risk of plant drought stress. This study determined whether lower plant density or preferentially redirecting rainfall to plants on green roofs could reduce drought stress without reducing rainfall retention. Plant density was manipulated, and metal structures were installed above the substrate surfaces to redirect the flow of rainwater towards plants (runoff zones). Green roof modules were used to test three plant density treatments: unplanted, half-planted (10 plants/m2) and fully-planted (18 plants/m2), and two runoff zone treatments which were installed in unplanted and half-planted modules. It was expected that 1) green roofs with greater plant density would experience more drought stress (i.e., lower leaf water status), and 2) green roofs with runoff zones would show higher ET and hence retention compared with those without runoff zones, as water will be directed to plants (run-on zones), facilitating growth. Contrary to the hypothesis, evapotranspiration (ET) and rainfall retention were similar for half-planted and fully-planted modules, such that ∼82 % of applied rainfall was retained. While both vegetation treatments dried out the substrates before rainfall was applied, the fully-planted modules dried out quicker and showed significantly lower leaf water status than half-planted modules. This indicates that planting at lower density may reduce plant drought stress, without reducing rainfall retention. Installing runoff zones marginally reduced ET and rainfall retention, likely due to shading by the runoff zone structures reducing evaporation from the substrate. However, runoff also occurred earlier where runoff zones were installed as they likely created preferential flow paths that reduced soil moisture and therefore ET and retention. Despite reduced rainfall retention, plants in modules with runoff zones showed significantly higher leaf water status. Reducing plant density therefore represents a simple means of reducing plant stress on green roofs without reducing rainfall retention. Installing runoff zones on green roofs is a novel approach that could reduce plant drought stress, particularly in hot and dry climates, albeit at a small cost of reduced rainfall retention.

An improvement in drainage flow equation of EPA SWMM green roof module.

Green roofs are among the important green infrastructures which decrease the negative impacts of urbanization. In this study, the green roof modeling capability of U.S. Environmental Protection Agency Storm Water Management Model (EPA SWMM) is evaluated and the modeling methods used in EPA SWMM, which need improvements, are determined. In particular, the drainage flow, which is originally calculated with Manning's equation in SWMM, is improved by introducing the drainage mat void thickness and adapting a new value for the exponential coefficient of depth in the equation. In addition, the capability of the percolation equation is further investigated, i.e., the value of the coefficient of the exponential function of soil moisture content that considers the percolation through the soil layer is determined for different substrates using the existing unsaturated hydraulic conductivity and soil moisture content data from steady-state tests. A comparison of the improved equation of drainage flow results with the existing experimental data shows that the improved equation represents the drainage flow more accurately than the one used in EPA SWMM.

Integrating microbial fuel cell with sedum green roof for stormwater retention and renewable energy generation

Climate change brings frequent and intense storms, which challenge aging stormwater infrastructures. As a sustainable stormwater solution, green roofs are being more frequently used in urban areas. However, high installation and maintenance costs have limited applications of green roofs on a large scale. A plant microbial fuel cell (P-MFC) is a novel technology that uses bacteria living around the root of plants to generate electricity. This study explores the integration of P-MFCs with an extensive green roof module for the dual benefit of stormwater runoff reduction and renewable energy generation. While most P-MFC systems in the literature are based on flooded plants, the green roof MFC developed in this study uses sedum plants which are among the most common vegetation layers for green roof solutions. We hypothesized that MFC efficiency could be improved by introducing a water storage layer and capillary sub-irrigation. Moreover, the capillary irrigation wick can function as a salt bridge to further enhance power generation. Three prototypes were fabricated to test our hypotheses, including a control unit without sub-irrigation and two units with capillary irrigation and one with additional salt bridge configuration. Experiments demonstrated that capillary irrigation and the salt bridge configuration significantly increased P-MFC’s power density and decreased the internal resistance. The research demonstrated that green roof modules with integrated P-MFCs can be a renewable energy generator, promoting the adoption of green roofs as sustainable solutions for climate resilience by simultaneously reducing storm floods, capturing carbon dioxide (CO2) in the atmosphere, and producing green electricity.

Green roofs sown with an annual plant mix attain high cover and functional diversity regardless of irrigation frequency

Annual plant species have great potential on green roofs as many are highly attractive, fast and cheap to establish via sowing and can provide rapid cover and growth, which is important for ecosystem service provision. While irrigation is essential for survival and growth of annual plants in seasonally hot or dry climates, it is also important to minimize water use as availability is often limited. Therefore, we evaluated how irrigation frequency affects plant cover, species abundance, richness and diversity, plant traits and functional diversity of a 16 species mixture of Australian annual species (4 g m−2 ~ 2100 seeds m−2) sown onto thirty 0.25 m2 green roof modules. The experiment was carried out in Melbourne, Australia, from January (summer) to July (winter) 2020. After a 2-month irrigated establishment phase (to ensure germination and seedling establishment), three irrigation treatments (2, 4 and 6 days between irrigation) were applied to the modules for three months. Plant cover was reduced at lower irrigation frequency (6 days), but ≥ 80% plant cover was achieved in all irrigation treatments. There was no effect of irrigation frequency on species abundance and richness; however, abundance, richness and diversity reduced over time, likely due to competition effects. Plant height and leaf area were also reduced by lower irrigation frequency. At the community level, functional diversity was unaffected by irrigation frequency. Our results indicate that green roofs sown with a mixture of annual plants can achieve good plant coverage, as recommended by green roof guidelines, and maintain high diversity when minimally irrigated in their first growing season.

The rainwater retention mechanisms in extensive green roofs with ten different structural configurations.

Rainfall infiltration, rainwater retention, runoff and evapotranspiration (ET) are important components of the water balance in green roofs. These components are expected to be influenced by variations in the structural configurations (i.e., substrate layers) of green roofs. This study explores the influence of layered soil and green roof configurations on the rainwater retention capacity (RRC) of the roofs as compared to conventional improvements (i.e., soil conditioning and enhanced substrate depth). Ten different extensive green roof modules were designed by varying the substrate materials, substrate depths, storage/drainage layers and vegetation layers. For all modules, the RRCs ranged from 34 to 59%. The RRCs of layered soil were 1-4% higher than that for single-layer soil. The RRC increased by 13% in the presence of a water storage module. It can be concluded that highest RRC corresponds to a combination of high-permeability soil in the upper layer along with a relatively large water holding capacity in the deep layer. Water storage layer and layered soil could significantly delay the water stress in vegetation. The importance of wick irrigation, vegetation types, back-to-back rain events and the ET rate on the RRC were also discussed.

Are succulence or trait combinations related to plant survival on hot and dry green roofs?

The many ecosystem services that green roofs can provide rely on good plant coverage and plant survival, which is challenging in hot and dry climates. While true succulents like Sedum spp. have been shown to survive well on green roofs, there are limited studies relating individual traits or trait combinations to survival in other life-forms. Succulence is a rarely studied trait that describes plant water storage in leaves, stems and roots, regardless of life-form. This means that succulence can occur in plants which are not considered to be true succulents like Sedum or Crassula species. Improving water availability through succulence may improve survival on unirrigated green roofs, but succulence, as a trait, has rarely been investigated in plants which are not true succulents. We investigated whether succulence or trait combinations can relate well with survival and could be used to improve plant selection for different substrate depths on hot and dry green roofs. We conducted two experiments with the same 11 Mediterranean species (five herbs, three sub-shrubs and three shrubs); (1) a pot experiment to determine traits under well-watered conditions including: succulence, leaf lethal temperature, water use, root:shoot ratio and leaf area. These individual traits and the combinations of all these traits were used in the analyses of this experiment; and (2) a green-roof module experiment to determine survival in four substrate depths (10, 15, 20, and 25 cm). Survival was not related to succulence, indicating that increased internal water storage in non-succulent plants does not per se lead to greater survival in extreme conditions. Survival was also not related to individual traits relating to water use and leaf heat tolerance or trait combinations. Nevertheless, plants in the same functional groups had similar survival, which suggests plants with similar trait combinations can have similar survival on green roofs.

Experimental evaluation of the rainfall retention and inorganic pollutant mitigation effect by dual-layer and polyacrylamide-modified green roofs.

Research on substrate layer modification and filler configuration is an important direction for improving the retention and interception efficiency of green roofs. In this study, four green roof modules were established using peat soil, vermiculite, and zeolite as the main substrate layer. In addition, a polyacrylamide (PAM) modifier was added and mixed with these substrates. By simulating seven rainfall events, this study calculated and analyzed the outflow of each green roof as well as the average event mean concentration (EMC) and cumulative outflow quantity (COQ) of turbidity, ammonia nitrogen ([Formula: see text]), nitrate nitrogen ([Formula: see text]), total nitrogen (TN), and total phosphorus (TP). At the same time, the nitrogen mass balance of each green roof was analyzed. The experimental results showed that the interception capacity of the LP module was higher than the unmodified green roofs under heavy rain conditions. The modules also showed an improved capacity to inhibit the leaching of [Formula: see text]; therefore, TN was effectively suppressed. However, suppression of [Formula: see text] did not significantly improve. The outflow turbidity from the MP and LP modules was low and stable, and the TP concentration showed no apparent change. After the simulated rainfall experiment with the rainfall of 426.3 mm, the proportion of TN leaching out of the LP module was at its lowest (0.85%), and the residual proportion of TN reached 80.7%. Overall, the addition of PAM to the dual-substrate layer can better form the soil aggregate structure, to improve the retention and purification effect of the extensive green roofs.

Stormwater retention and detention performance of green roofs with different substrates: Observational data and hydrological simulations

Green roofs are widely considered as a promising nature-based solution for urban stormwater management. In this study, the stormwater retention and detention performance of 6 green roof modules with different types and depth of substrates at Beijing, China was investigated through 3-year continuous monitoring. The Hydrus-1D was applied to further explore the stormwater management performance of green roofs under extreme storms. The average event-based stormwater retention and detention rates of the green roofs with 10 cm substrates ranged between 81% and 87%, and 83%–87%, respectively; and the average time delays in runoff generation and peak discharge ranged between 82 and 210 min, and 63–131 min, respectively. Green roofs with 15 cm depth of substrates offered higher stormwater retention and peak runoff attenuation rates than those with 10 cm substrates. However, due to the high frequency (55 out of total 92) of light rainfall events (<10 mm) and short antecedent dry weather periods (3.8 days in average), no significant difference was found on stormwater control performance of those green roofs. The Hydrus-1D simulations revealed that green roof stormwater retention rate decreases exponentially with return periods of extreme storms but increases with substrate depth. There exists a critical depth of substrates and further increases in substrate depth beyond this critical value could not bring much improvement in stormwater retention performance of green roofs. The application of extensive green roofs with 10–15 cm substrates provides promising stormwater retention and detention performance in highly urbanized area of Beijing.

Green roof evapotranspiration rates and stormwater control under subtropical climate: a case study in Brazil

ABSTRACT In this study a long-term field experiment evaluating evapotranspiration rates from irrigated and non-irrigated green roof modules, as well their impacts on stormwater control was accomplished. Six green roof modules (3 irrigated and 3 non-irrigated) vegetated with S. rupestre were monitored throughout 8 months in southern Brazil. Four non-vegetated modules (2 irrigated and 2 non-irrigated) were simultaneously assessed to understand the role of the vegetation in the whole process. The average evapotranspiration under water-stress (ETr) was 2.6 mm.day-1, while mean evapotranspiration under water-abundance (ETp) was 2.8 mm.day-1. Higher evapotranspiration rates were observed during summer, increasing the substrate storage capacity, although ETr amount along the seasons was very similar, mainly affected by climatic conditions. The long-term analysis showed that 47% of the total rainfall was converted into runoff, 21% was retained in the green roof modules and 32% was released through evapotranspiration, reinforcing the importance of vegetation as a mechanism for improving stormwater control benefits. The results of this research also allowed the establishment of a crop coefficient (Kc) time series, with a monthly average of 0.9 which permits the S. rupestre evapotranspiration to be preliminarily estimated by using equations developed for reference culture without the need of monitoring.

A physics-based routing model for modular green roof systems

The ability of green roof systems to impact stormwater runoff from buildings has been covered in many research studies. However, a lot of these studies looked at long-term retention, with much less work focused on how to model a green roof's response to larger design storms. Work that has examined flow routing for individual rainfall events has focused on empirical routing models that are tuned to the specific roof being modelled. This paper presents a new physics-based model for flow routing based on the green roof module geometry and soil properties, which requires only a single discharge coefficient to be measured. The results of this model were compared with the results of a series of experiments to quantify a modular green roof system's hydraulic response to drawdown and steady rainfall.

An experimental and modeling study of evapotranspiration from integrated green roof photovoltaic systems

Co-locating green roof (GR) systems with photovoltaic panels (PV) can allow optimal use of roof space for energy production as well as stormwater management. Models for evapotranspiration from integrated Green Roof Photovoltaic Systems (GR-PV) are needed for the design of GR-PV systems. Existing evapotranspiration models can not be used for this purpose due to complex sunlight-shading and wind-sheltering effects. PV panels partially block direct solar radiation onto underlying GR modules affecting evapotranspiration (ET) rates. Additionally, PV panels can cause wind profiles to differ from the profiles assumed in existing ET models. In this study, ET rates from an unsheltered GR module were compared with ET rates from GR modules sheltered by an overhead PV panel. ET rates were lower in the sheltered GR module than in the unsheltered GR module. A new ET model was developed incorporating reduction factors to apply to net radiation and wind speed beneath an array of PV panels. The reduction factors are based on the length, height, slope, and spacing of PV panels, as well as the diurnal characteristics of sun and wind. Predictions of ET rates from the new ET model compared well to ET rates determined from lysimeter measurements from GR modules below an array of PV panels. The sensitivity of the new GR-PV system ET model for the key design parameters, including PV height, slope, length, and row-spacing was investigated. The ET rates are most sensitive to the height above the GR and the length of PV panels in GR-PV systems.

Cooling Benefits of an Extensive Green Roof and Sensitivity Analysis of Its Parameters in Subtropical Areas

The present study aims to further demonstrate the cooling benefits of an extensive green roof (EGR) and fill the gap existing in the literature in terms of a sensitivity analysis of an EGR, especially in subtropical areas. First, onsite measurements were performed. The results indicated that the peak air temperatures in the chamber with the EGR were 4.0 °C and 1.9 °C lower, respectively, compared to those in the chamber with a bare roof on sunny and rainy days. Moreover, the EGR decreased the daily electricity consumption from air conditioning by up to 16.7% on sunny days and 6.7% on cloudy days. Second, the measured values were employed to validate the green roof module (GRM) in EnergyPlus. The results demonstrated that the GRM yielded accurate results in quantifying the cooling benefits of the EGR. Finally, we selected 16 factors of the EGR, each with four levels, to perform the sensitivity analysis. Range and variance analyses revealed that the factors that most significantly impacted the EGR performance were the R-value of roof construction, substrate (soil) thickness, the thermal conductivity of dry substrate, the leaf area index, leaf emissivity, and the solar absorptance of the substrate. These factors contributed 90.8% to the performance index.

Is plant survival on green roofs related to their drought response, water use or climate of origin?

Green roofs are novel urban ecosystems with shallow substrate depths and low water availability. Hence, it is critical to select green roof plants that can survive water-deficits, particularly in climates with hot and dry summers. Shrubs are perennial plants which can be drought resistant and may be suitable for green roofs. However, studies about survival and health of shrubs are limited. The aim of this study was to determine whether plant climate of origin aridity, drought response and water use strategies could be used to select shrubs which can survive on green roofs that experience water-deficit. We selected 15 shrub species from a range of climates (dry, mesic and wet) and planted them together in 20 replicate green roof modules with 130 mm deep substrate. We monitored substrate water contents, plant minimum water potentials (ψmin), health (visual score), percentage survival and related survival with their turgor loss point (ψtlp) and water use strategies (evapotranspiration rates in a related glasshouse experiment). We also determined whether plants could recover after dry periods by rewatering after the summer. Mean gravimetric soil water content decreased to approximately 5% after summer drought, which resulted in mortality. Overall, survival ranged between 10% and 100% for the 15 species. However, survival was not related to their ψtlp or water use strategies. While shrubs from more arid climates had lower ψmin in response to dry substrates, this did not result in greater survival and health. Following rewatering, only four shrub species resprouted. Hence, as plant drought response, water use strategy and climate of origin were not strongly related to survival, we suggest survival on green roofs is likely to be determined by a combination of physiological traits. Emergency irrigation for shrubs growing on green roofs in hot and dry climates is recommended during summer to keep them alive.

The transferability of SWMM model parameters between green roofs with similar build-up

While extensive green roofs are popular measures for reducing and delaying stormwater runoff, design tools are needed to better predict roof performance based on material properties, geometry and climate. This paper investigates the EPA’s Storm Water Management Model’s (SWMM) green roof module for this purpose based on observed runoff from several roofs with different build-ups, geometry, and climates. First, the general model performance was investigated and secondly transferability of model parameters for similar roofs but different geometries and climates was tested. Individual models reproduced runoff hydrographs well (NSE 0.56–0.96), while the long-term modelling showed relatively large volume errors most likely due to insufficient representation of evapotranspiration in the model. Model parameters obtained at one site were only partly transferable to similar roof build-up at other sites. Transferability was better from models calibrated with wetter climates and higher intensity events to drier climates, than the opposite way. Multi-site calibration resulted in model parameters performing well for most sites, giving model parameters that could be used for the design of similar roof build-ups in comparable climates. However, large variability in obtained model parameters, large volume errors and the fact that the calibrated model parameters did not directly correspond to measured material properties, place concerns on the generality of the SWMM green roof module as a design tool.

Factors Affecting Runoff Retention Performance of Extensive Green Roofs

The runoff retention effectiveness of 10 extensive green roof (EGR) modules (100 mm substrate planted Sedum lineare Thunb.) were analyzed in Beijing for 22 rainfall events (2.4–46.4 mm) from 1 July to 30 September 2017. Differences between minimum inter-event dry periods, module scales, substrate hydraulic conductivity and depths, drainage layer types and rainfall characteristics were examined to study their correlation to the retention performance of EGRs. In general, EGRs with lower substrate hydraulic conductivity, deeper substrate and lower rainfall depth had higher runoff retention performance. By comparsion, no siginificant correlation was found between rainfall duration, prior dry period, average rainfall intensity, drainage layer type and EGR runoff retention rate. Analyses of variance (ANOVA) and Tukey tests supported these results. Low or moderate rainfall (&lt;15 mm) may or may not have an effect, but heavy rainfall (&gt;25 mm) definitely affects the EGR retention performance of the next rainfall event.

Rainwater retention effect of extensive green roofs monitored under natural rainfall events – a case study in Beijing

Abstract The rainwater retention and peak flow reduction effect of seven extensive green roof (EGR) modules were studied in Beijing under natural rainfall events from May to September 2015. Monitored EGR modules had a layer of vegetation widely planted in northern China and a substrate layer with a thickness of 20 or 50 or 100 mm. The EGRs effectively retained rainwater, and regression equations of the potential retention capacity as a function of rainfall depth were developed for five EGR modules, which show that generally the capacity decreased as rainfall depth increased. The EGR with Sedum lineare Thunb and 100 mm improved soil had relatively higher average retention capacity (61.8%) than others, but all EGR modules had similar retention for an extraordinary rainfall event of 114.4 mm. For rainfall events less than 15 mm, EGR modules had 100% rainfall retention most of the time. The reduction in peak runoff rate ranged from 30.8% to 85.4%. The EGRs with Sedum lineare Thunb using 20 mm improved soil and 50 mm either pastoral soil or ultra-low weight substrates have similar peak reduction (51.3–58.2%). The EGRs with Sedum lineare Thunb have better rainfall retention and peak reduction than EGRs with Angiospermae or Sedum aizoon L.

Thermal Comfort Performances of a Green Roof Modular System Fixed on Gable Roofs

Urbanised areas are tend to heat up more than neighborhoods as consequences of global warming and urban heat island effect due to high built up areas. Moreover, buildings are the most energy consumptive assets in energy systems. Green roofing is a popular strategy for passive cooling of buildings in present green building industry and it has become the best solution to overcome problems related to thermal comfort. A conventional green roof made up with the combination of vegetation layer, growing media, drainage layer and root barrier layer add a huge weight up on the existing roofs. Hence, green roof modular system is more efficient in cost and performances basis with less weight as separated by prefabricated or non−prefabricated novel method. This study evaluated the effect of fixed green roof modular system to an existing building to ensure the thermal comfort performances of outdoor and indoor conditions of the building by innovating portable frame network and new growing media for green modules with low weight, low cost and easy maintenance. Developed module’s unit weight was 400 −450 g and it covered an area of 412.5 cm2. It was fabricated with fiber glass and a frame network was developed using canvas−rubber mixed materials with a unit weight of 622.5 g. Growth medium was prepared by using rubber and coir mixed material. Ipomea aquatica, Centella asiatica and Alternanthera sessilis were used as testing vegetation for the developed green roof modules. Leaf area (LA) and number of leaves were used as the parameters to select the best plant variety for the green roof. Subsequent thermal performance parameters of the green roof were analysed by comparing it with a normal roof of the same building. Leaf area of C. asiatica was significantly higher than I. aquatica and A. sessilis. Plant height, LA and number of leaves are the main factors that control the penetration of solar radiation; hence it influences the temperature. By considering statistical analysis and above facts, C. asiatica was selected as the best plant variety for the modules. A maximum indoor and outdoor temperature difference was reported after implementing the green roof modular system as 3 C. Control roof showed a maximum temperature difference of 2.3 C between indoor and outdoor. The maximum relative humidity difference between inside and the outside roof was recorded as 3.5% while control roof was given 3.3%.Therefore green roof modular system developed with fiberglass and frame network with coir-rubber mixed growing media for Centella asiatica can be suggested to enhance the thermal comfort of indoor and outdoor environments. Keywords: Green roofs, Green roof modules, Growing medium, Leaf area, Portable frame network