Abstract
Urban vegetation is known to be effective in mitigating the Urban Heat Island (UHI) effect and reducing building energy use, specifically that associated with cooling. However, to quantify urban trees' cooling effect, the influence of their characteristics on cooling effectiveness and the corresponding building energy use needs to be assessed quantitatively and reflected in energy simulation efforts. In this study, a modelling framework is introduced to facilitate the integration of high-resolution geometries for trees in urban energy simulation models. A preliminary study of this modelling framework showed that our enhanced tree models can predict cooling loads that are as much as 2.2% lower than those predicted with the simplified tree models that are typically used. This enhancement in modelling can address current shortcomings for predicted and actual energy consumption of buildings.
| Original language | English (US) |
|---|---|
| Title of host publication | BS 2021 - Proceedings of Building Simulation 2021 |
| Subtitle of host publication | 17th Conference of IBPSA |
| Editors | Dirk Saelens, Jelle Laverge, Wim Boydens, Lieve Helsen |
| Publisher | International Building Performance Simulation Association |
| Pages | 2284-2291 |
| Number of pages | 8 |
| ISBN (Electronic) | 9781775052029 |
| DOIs | |
| State | Published - 2022 |
| Externally published | Yes |
| Event | 17th IBPSA Conference on Building Simulation, BS 2021 - Bruges, Belgium Duration: Sep 1 2021 → Sep 3 2021 |
Publication series
| Name | Building Simulation Conference Proceedings |
|---|---|
| ISSN (Print) | 2522-2708 |
Conference
| Conference | 17th IBPSA Conference on Building Simulation, BS 2021 |
|---|---|
| Country/Territory | Belgium |
| City | Bruges |
| Period | 9/1/21 → 9/3/21 |
Bibliographical note
Funding Information:street trees, there are relatively few comprehensive urban forest inventories that include so much information on canopy dimensions, the degree to which the canopy is filled with leavers, and fewer still include such data for trees on private properties. It may be that the development of specific empirically-based models will allow calibration of models using other available data (such as LiDAR imagery with detail for tree canopy shape and size) in the future. Further cross-variable simulations are planned to explore and refine these preliminary outcomes. Acknowledgments The work presented in this paper was funded by the 2016 Iowa State University Presidential Interdisciplinary Research Initiative (PIRI) on Data-Driven Science and by McIntire-Stennis funds. Farzad Hashemi, Manon Geraudin, and Sedigheh Ghiasi are thanked for their help with umi simulations. References ASHRAE. (2009). Ashrae Climatic Design Conditions 2009/2013/2017: Des Moines Intl Ap, Ia, Usa (Wmo: 725460). 2009 ASHRAE Handbook - Foundamentals (SI). http://ashrae-meteo.info/v2.0/?lat=41.54&lng=-93.67&place=%27%27&wmo=725460 ASHRAE. (2020). 2019 ASHRAE Handbook. Oak Ridge National Lab (ORNL). Davis, A. Y., Jung, J., Pijanowski, B. C., & Minor, E. S. (2016). Combined vegetation volume and “greenness” affect urban air temperature. Applied Geography, 71, 106–114. Drehobl, A., & Ross, L. (2016). Lifting the high energy burden in America’s largest cities: How energy efficiency can improve low-income and underserved communities. American Council for an Energy-Efficient Economy, April, 56. https://aceee.org/research-report/u1602 EnergyPlus. (n.d.). Weather Data Download - Des Moines Intl AP 725460 (TMY3). https://energyplus.net/weather-location/north_and_central_america_wmo_region_ 4/USA/IA/USA_IA_Des.Moines.Intl.AP.725460_ TMY3. Fedoruk, L. E., Cole, R. J., Robinson, J. B., & Cayuela, A. (2015). Learning from failure: understanding the anticipated–achieved building energy performance gap. Building Research & Information, 43(6), 750– 763.
Publisher Copyright:
© International Building Performance Simulation Association, 2022
