Conference Editor

Jianshun Zhang; Edward Bogucz; Cliff Davidson; Elizabeth Krietmeyer

Keywords:

Urban Microclimate, Urban heat island, Outdoor thermal comfort, Monitoring, Environmental quality.

Location

Syracuse, NY

Event Website

http://ibpc2018.org/

Start Date

25-9-2018 1:30 PM

End Date

25-9-2018 3:00 PM

Description

The rapid urbanization of the last century coupled with local climate change imputable to anthropogenic actions triggered a huge research effort aimed at investigating urban microclimate. Typically, cities present a variety of microclimates due to the internal variation of their landscapes in terms of morphology, surfaces properties, presence of greenery, etc. Location-specific microclimate conditions affect both (i) building energy needs and (ii) citizens’ quality of life. For these reasons, a small-scale analysis from the citizen perspective with high-time-resolution environmental data is required. Recent studies tried to reach that level of precision by using remote sensing, movable observational transects or dense network of weather stations located in specific points of the urban settlement. Within this framework, the current study presents a new bottom-up methodology which aims at identifying granular microclimates within the same built environment. The method consists of a cluster analysis of experimental data collected by a wearable miniaturized weather station which allows the monitoring of outdoor parameters at the pedestrian height and with high-time resolution. Experimental campaigns were conducted in five different case studies, where a planned monitoring path was repeated at different times during the day. The heterogeneity of the context demonstrates the replicability of the proposed method, suitable for clustering different areas of a same urban context characterized by variable local microclimate. The study contributes to better understand the variability of building boundary conditions for energy need prediction and indoor/outdoor environmental comfort assessment.

Comments

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DOI

https://doi.org/10.14305/ibpc.2018.gb-3.03

Creative Commons License

Creative Commons Attribution-Noncommercial 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 4.0 License.

COinS
 
Sep 25th, 1:30 PM Sep 25th, 3:00 PM

New microclimate monitoring method and data process for investigating environmental conditions in complex urban contexts

Syracuse, NY

The rapid urbanization of the last century coupled with local climate change imputable to anthropogenic actions triggered a huge research effort aimed at investigating urban microclimate. Typically, cities present a variety of microclimates due to the internal variation of their landscapes in terms of morphology, surfaces properties, presence of greenery, etc. Location-specific microclimate conditions affect both (i) building energy needs and (ii) citizens’ quality of life. For these reasons, a small-scale analysis from the citizen perspective with high-time-resolution environmental data is required. Recent studies tried to reach that level of precision by using remote sensing, movable observational transects or dense network of weather stations located in specific points of the urban settlement. Within this framework, the current study presents a new bottom-up methodology which aims at identifying granular microclimates within the same built environment. The method consists of a cluster analysis of experimental data collected by a wearable miniaturized weather station which allows the monitoring of outdoor parameters at the pedestrian height and with high-time resolution. Experimental campaigns were conducted in five different case studies, where a planned monitoring path was repeated at different times during the day. The heterogeneity of the context demonstrates the replicability of the proposed method, suitable for clustering different areas of a same urban context characterized by variable local microclimate. The study contributes to better understand the variability of building boundary conditions for energy need prediction and indoor/outdoor environmental comfort assessment.

https://surface.syr.edu/ibpc/2018/GB3/3

 

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