Comparison of thermal performance between green roofs and conventional roofs

Polo-Labarrios, M.A.; Quezada–García, S.; Sánchez–Mora, Heriberto; Escobedo-Izquierdo, M. Azucena; Espinosa-Paredes, Gilberto

doi:10.1016/j.csite.2020.100697

Cited by 29 publications

(9 citation statements)

References 72 publications

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“…As the day started, both the CR and PBGR started to absorb heat from 8 a.m. after experiencing cold at night. From 8.30 a.m. to 12 p.m., some plants did not show any cooling effect; instead, they sustained elevated temperatures compared to the CR at both 15 and 60 cm, similar to previous studies [ 57 , 66 ]. The PBGR absorbed this heat in summer through the soil substrate and raised the temperature and humidity of the surrounding microclimate.…”

Section: Resultssupporting

confidence: 90%

Monitoring of a Productive Blue-Green Roof Using Low-Cost Sensors

Akhie,

Joksimovic

2023

Sensors

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Considering the rising concern over climate change and the need for local food security, productive blue-green roofs (PBGR) can be an effective solution to mitigate many relevant environmental issues. However, their cost of operation is high because they are intensive, and an economical operation and maintenance approach will render them as more viable alternative. Low-cost sensors with the Internet of Things can provide reliable solutions to the real-time management and distributed monitoring of such roofs through monitoring the plant as well soil conditions. This research assesses the extent to which a low-cost image sensor can be deployed to perform continuous, automated monitoring of a urban rooftop farm as a PBGR and evaluates the thermal performance of the roof for additional crops. An RGB-depth image sensor was used in this study to monitor crop growth. Images collected from weekly scans were processed by segmentation to estimate the plant heights of three crops species. The devised technique performed well for leafy and tall stem plants like okra, and the correlation between the estimated and observed growth characteristics was acceptable. For smaller plants, bright light and shadow considerably influenced the image quality, decreasing the precision. Six other crop species were monitored using a wireless sensor network to investigate how different crop varieties respond in terms of thermal performance. Celery, snow peas, and potato were measured with maximum daily cooling records, while beet and zucchini showed sound cooling effects in terms of mean daily cooling.

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Section: Resultssupporting

confidence: 90%

Monitoring of a Productive Blue-Green Roof Using Low-Cost Sensors

Akhie,

Joksimovic

2023

Sensors

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“…New developments are often made at the expense of green areas [1] and green roofs are a sustainable solution to mitigate the effects of urbanization by replacing conventional roofs with vegetation and soil [2].…”

Section: Introductionmentioning

confidence: 99%

Theoretical Analysis and Comparison of the Thermal Performance, Construction Costs, and Maintenance Complexity between a Conventional and an Intensive Green Roof

Juricic¹,

Krstić

Čulo

2021

Journal of Engineering

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In this paper, a comparison between a conventional flat roof and an intensive green roof was made. Emphasis was on thermal conductivity of individual layers, the calculation of thermal resistance, and calculation of the thermal transmittance coefficient through both roof variants. The calculations for the two analysed roof variants were made for a building located in the town of Rijeka on the Adriatic coast. This paper also presents the construction technology comparison of the analysed roof variants. The construction cost was also analysed for both roof variants together with time needed for the execution of variant solutions. Finally, maintenance plans for both roof variants were presented in this paper. The results show that the construction costs of an intensive green roof are higher than the construction costs of a conventional flat roof and that the maintenance of the intensive green roof is more complex. On the other hand, the results of the analysis also show that constructing a green roof will result in more energy savings in the long term than in the case of constructing a conventional flat roof. In addition, there are several other benefits that go in favour of constructing an intensive green roof. Most prominent among those benefits are environmental and social benefits.

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“…For instance, as noted in Ref. [34], evapotranspiration has been quantified in green roof literature using the Penman-Monteith equation [35], the Priestley and Taylor method [36], the Hargreaves equation [37], the ASCE Penman-Monteith equation [38], and the BOWEN ratio [39]. Convection over green roof vegetation has been quantified using versions of Newton's law of cooling whereby parameters such as leaf area index (LAI) have been incorporated as weighting factors that consider leaf-dependent changes in effective exterior surface area [40]; studies have used empirical relations describing wind-and ambient temperature-dependent convection coefficients derived for green roof vegetation [41], [42].…”

Section: Literature Reviewmentioning

confidence: 99%

“…Meanwhile, conduction in green roof systems has been mainly considered in the growth substrate, though Ref. [37] has considered conduction through the vegetation itself. Nevertheless, it is well understood that conduction through soil varies as a function of moisture content.…”

Section: Literature Reviewmentioning

confidence: 99%

“…3.9 [67]. where ρplants (582 kg/m 3 ) and Cp,plants (4800 J/kg• °C) are the density and specific heat capacity of the plants, respectively [37]; ρair (1.184 kg/m 3 ) is the density of air; dcan (0.1 m) is the assumed height of the canopy layer, and fveg (m 3 /m 3 ) is the volumetric fraction of the foliage within the canopy layer. Note that -although fveg and LAI both represent vegetative density in three and two dimensions, respectively -these variables are not intrinsically linked in the model and are instead estimated independently.…”

Section: Rc Model Developmentmentioning

confidence: 99%

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Data-driven Modeling of Green Roof Thermal Performance in Ottawa, Canada.

Gunn¹

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This research investigates the application of inverse green roof models to both characterize green roof thermophysical properties and simulate the heat flux through the roof assembly. The first chapter of this thesis presents a preliminary analysis of green roof thermal performance in Ottawa, Canada, using two years of measured data, wherein thermal performance is defined as the percent reduction in total monthly heat exchange promoted by the green roof, relative to that through an adjacent conventional roof. Climatic factors influencing thermal performance are discussed on a seasonal basis, concluding that the green roof functioned best during warmer months when evapotranspiration was likely to be greatest. Thermal performance ranged between 31 -63% from May through September, with reduced performance during the colder months. In chapter 2, two inverse models of varying spatial discretization are developed for the same green roof: (1) a resistor-capacitor (RC) thermal network model, and (2) an implicit finite difference (FD) model.Each model was calibrated using monthly data from May to September in 2016 by employing a genetic algorithm to extract the thermophysical properties of the green roof soil and canopy layers via multi-linear regression. The difference in spatial resolution between each model was identified as an influential factor to thermophysical property estimation during calibration. The calibrated models were used to predict hourly rates of heat flux through the structural component of the green roof over each month of the study period, resulting in a root-mean-squared-error between 0.51 -1.0 W/m 2 and 0.41 -0.81 W/m 2 for the RC and FD models, respectively. Both models were validated against 5 continuous months of data from 2017, demonstrating that inverse modelling can successfully generate realistic thermophysical green roof properties.

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Comparison of thermal performance between green roofs and conventional roofs

Cited by 29 publications

References 72 publications

Monitoring of a Productive Blue-Green Roof Using Low-Cost Sensors

Monitoring of a Productive Blue-Green Roof Using Low-Cost Sensors

Theoretical Analysis and Comparison of the Thermal Performance, Construction Costs, and Maintenance Complexity between a Conventional and an Intensive Green Roof

Data-driven Modeling of Green Roof Thermal Performance in Ottawa, Canada.

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