Yara Elborolosy

Mrs. Yara Elborolosy


Research Focus & Metrics

Academic Career Length

9Years (2018-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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23 October 2018 in Water
Verified
Journal Article
Open access
PDF file
NANoura Abualfaraj
Noura Abualfaraj
JCJoseph Cataldo
Joseph Cataldo
YEYara Elborolosy
Yara Elborolosy
DFDaniel Fagan
Daniel Fagan
SWSloane Woerdeman
Sloane Woerdeman
FMFranco Montalto
Franco Montalto
Drainage from the 27,316-m2 Jacob K. Javits Convention Center (JJCC) green roof was investigated in the field to quantify the system’s long-term rainfall-runoff response. The JJCC hosts one of the largest extensive green roofs in the United States. Utilizing four years of rooftop monitoring data collected using a weather station, custom designed and built drainage systems, three Parshall flumes equipped with pressure transducers, and weighing lysimeters, this study quantified the 25.4-mm-deep green roof’s ability to decrease the volume and peak rate of runoff. With parameters derived from the site, the Environmental Protection Agency Stormwater Management Model (EPA-SWMM) predicted event total runoff volume and event peak runoff rates to within +10% to −20% and +25% to −15% of the observations, respectively. The analysis further indicated that approximately 55% of the cumulative precipitation that fell on the JJCC extensive green roof during the monitoring period (warm weather months, June 2014–November 2017) was captured and retained. The average percent retained on an event-basis was 77%, and average event runoff coefficient was 0.7, implying a substantial reduction in the volume and rate of runoff generated from the roof compared to the pre-green roof condition, when most, if not all, of the precipitated water would have immediately resulted in runoff. Our research suggests that, on average, 96% of rainfall events 6.35 mm or less were retained within the green roof, whereas 27% of the total event volume was retained for events greater than 12.7 mm in depth. A sensitivity analysis suggests if the substrate depth were increased, better stormwater capture performance would be achieved, but only up 127 mm, whereas increased precipitation coupled with warmer temperatures as a result of climate change could decrease the performance by up to 5%, regardless of substrate depth. An equivalency analysis suggested that even shallow green roofs can significantly reduce the required stormwater detention volume that New York City requires on new development. This particular green roof appears to be more than 18 times as cost-effective as a subsurface cistern would be for managing an equivalent volume of stormwater in Midtown Manhattan.

6 June 2024 in Journal of Environmental & Earth Sciences
Verified
Journal Article
Open access
PDF file
JCJoseph Cataldo
Joseph Cataldo
YEYara Elborolosy
Yara Elborolosy
Several studies were compiled using data from physical models of green and black surfaces in the lab and the Cooper Union (CU) roof as well as green roof studies of the Javits Green Roof (JGR) measured over a six-year period. Observations were made with weather stations, custom designed draining systems and three partial flumes each equipped with a pressure transducer and weighing lysimeters. An infrared camera was used at the CU and JGR to collect thermal images to determine the effectiveness these roofs had for thermal buffering. A multiple regression curve was calculated relating the lysimeter mass and five independent variables, with the precipitation runoff and retention time being the most important variables. The surface of the black roof was compared to white and green roofs at CU. The temperature was significantly higher (over 70 °C) on the black roof clearly showing the advantage of using a green roof. The ET was calculated on the JGR using the Penman-Monteith (P/M) equations. The runoff hydrograph for the JGR was constant with an increase in precipitation and storage when the hydrograph dropped in response to the precipitation and storage. When the plots (185 square meters at JGR) were irrigated, the dry plots always had higher temperatures (above 15 °C during summer daytime). The ET is the controlling factor for temperature reduction on a vegetated green roof as shown in the JGR data. The relative humidity (RH) was measured in the CU lab and on the JGR and showed similar results. The RH dropped during higher temperatures and recovered at lower temperatures. The results of these studies at CU and JGR clearly show the benefits of using a vegetated green roof.

27 January 2024 in Journal of Environmental & Earth Sciences
Verified
Journal Article
Open access
PDF file
YEYara Elborolosy
Yara Elborolosy
HSHarsho Sanyal
Harsho Sanyal
JCJoseph Cataldo
Joseph Cataldo
Two methods of irrigation, drip, and sprinkler were studied to determine the response of the Javits green roof to irrigation. The control study was dry unirrigated plots. Drip irrigation consisted of irrigation tubes running through the green roof that would water the soil throughout and sprinkler irrigation used a sprinkler system to irrigate the green roof from above. In all cases, the irrigated roofs had increased the soil moisture, reduced temperatures of both the upper and lower surfaces, reduced growing medium temperatures and reduced air temperatures above the green roof relative to the unirrigated roof. The buffered temperature fluctuations were also studied via air conditioner energy consumption. There was a 28% reduction in air conditioner energy consumption and a 33% reduction in overall energy consumption between dry and irrigated plots. Values of thermal resistance or S were determined for accuracy and for this study, there was little change which is ideal. A series of infra-red and thermal probe measurements were used to determine temperatures in the air and sedum. It was determined that the sprinkler irrigation did a better job than the drip irrigation in keeping cooler temperatures within the green roof. A Mann-Whitney U test was performed to verify the variation in moisture temperatures buffering energy consumption. By getting a p-value < 0.05, it indicates that the model is accurate for prediction and medium temperatures were statistically different.