Summertime thermal conditions and senior resident behaviors in public housing: A case study in Elizabeth, NJ, USA

Tsoulou, Ioanna; Andrews, Clinton J.; He, Ruikang; Mainelis, Gediminas; Senick, Jennifer

doi:10.1016/j.buildenv.2019.106411

Cited by 27 publications

(22 citation statements)

References 53 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The technical inscription process of this test bed involves collecting thermal data from classifiable built environments, modeling microclimates, and producing tools for communicating and visualizing granular data. The policy inscription process involves collecting data on thermal phenomenology-people's experiences with heat, cold, humidity, and wind-which can be characterized using social science methods such as interviews, surveys, focus groups, 'thermal walks,' and ethnographic participant observation methods (Kuras et al 2017;Lau, Shi, & Yan-Yung Ng 2019;Tsoulou et al 2020). In this regard, both the technical and policy inscription processes align with the concept of precision governance, an administrative capacity in which policy decisions are enhanced with information about individual and collective preferences and contexts (Hondula et al 2018).…”

Section: Discussion: Socio-technical Network For Thermal Governancementioning

confidence: 99%

Thermally resilient communities: creating a socio-technical collaborative response to extreme temperatures

Hamstead

Coseo

AlKhaled

et al. 2020

Buildings and Cities

View full text Add to dashboard Cite

Extreme temperatures claim more lives than any other weather-related event, posing escalating socio-technical and governance challenges that few urban communities have addressed in a systematic, coordinated and comprehensive way. Scholars have only recently begun to investigate the granular scales at which distributions of thermal risk are produced, people's individual subjective thermal experiences and environmental justice dimensions of the hazard. Advances in research pave the way for concomitant improvements in management and policies, but bridges are needed to connect the thermal vulnerability knowledge base with place-based protective practices that are climatically, politically and culturally appropriate. The research presented in this paper uses actor-network theory (ANT) to describe the planning phase framework of a socio-technical collaborative for managing thermal extremes. The Thermally Resilient Communities Collaborative (TRCC) is a framework for planning and test-bed design phases of a thermal management system. Drawing lessons from two case studies, the framework examines how socio-cognitive spaces for collaboration change with technical and policy disruptions, and provides a way to design experiments that test how technical and governance interventions can enable collective action around urban thermal management. Practice relevanceThermal extremes claim more lives than all other weather events and pose an escalating socio-technical challenge. Often the problem is exacerbated by lack of clarity about organizational responsibilities and coordination between local governmental departments or agencies. The TRCC framework can be used to understand current practices, identify data gaps and create opportunities to engage in cross-sectoral management. This approach engages actors in identifying built environments and societal practices that create hazardous indoor and outdoor thermal conditions, develops effective ways to convey microclimate information and peoples' subjective thermal experiences to responders and prevention planners, and elevates experiences of marginalized communities. The TRCC describes how governance networks are harnessed to solve collective action problems by integrating new data, technology, and governance capacities. Two case studies indicate how this process was used to create capacities to protect vulnerable people from the impacts of extreme temperatures in two US cities: Tempe, Arizona, and Buffalo, New York.Thermally resilient communities 219 1. Background Thermal extremes pose an escalating socio-technical and governance challenge in cities across the globe. In the United States, prolonged periods of heat and cold claim more lives than all other weather-related events (Berko et al. 2014) and have significant impacts on urban ecosystems and infrastructure. Approximately 30% of the world's population is exposed to deadly heat and humidity for at least 20 days per year, and that percentage is expected to increase to 48-74% by 2100, depending on what emissions scenario occurs (M...

show abstract

Section: Discussion: Socio-technical Network For Thermal Governancementioning

confidence: 99%

Thermally resilient communities: creating a socio-technical collaborative response to extreme temperatures

Hamstead

Coseo

AlKhaled

et al. 2020

Buildings and Cities

View full text Add to dashboard Cite

show abstract

“…[11]- [14], [40] Location Geographical location attributes, such as climate zones, country, and energyrelated policy in place.…”

Section: Representation Of the Synthetic Occupant Populationmentioning

confidence: 99%

“…[16], [40], [43] Activities at work Indoor activities are pertaining to presence, movement, and use of appliances. Consume hot/cold drinks.…”

Section: Representation Of the Synthetic Occupant Populationmentioning

confidence: 99%

An ontology to represent synthetic building occupant characteristics and behavior

Putra

Hong

Andrews

2021

Automation in Construction

View full text Add to dashboard Cite

Since the introduction of the occupant behavior Drivers-Needs-Actions-Systems (DNAS) framework in 2013, researchers have used the framework or further developed it based on their case studies, which include efforts to collect new data on occupant behaviors. The effort is often costly for the relatively few new data points added. Problems emerge when the already collected data do not meet the modelers' interoperability requirements. Previous studies addressed this issue by developing more sophisticated ontologies that enable integration with other datasets and synthetic data methodologies that would meet unique research applications. This paper presents an extension of the DNAS framework for the representation of synthetic occupant data to support various applications and use cases across the building life cycle. An agent-based modeling application is one of our motivations that requires more elaborate characteristics of an occupantagent or a group-of-agent. The extension, built upon a review of the literature, introduces new elements to the framework that fall into five categories, including socio-economic, geographical location, activities, subjective values, and individual and collective adaptive actions. On-going research includes identifying occupant datasets and developing data fusion methods to generate synthetic occupants, as well as to demonstrate its applications in agent-based modeling coupled with building performance simulation.

show abstract

“…The Drivers-Needs-Actions-Systems (DNAS) framework environment includes actions such as thermostat adjustment, lighting adjustment, fans and portable heater operation, and moving between spaces. Other frameworks include detailed characteristics of occupants such as socio-conomic (Andrews, 2017;Kontokosta & Jain, 2015;Tsoulou et al, 2020), subjective values (Hong et al, 2020;Ortiz & Bluyssen, 2018), and activities (Hewitt et al, 2016;Malik & Bardhan, 2020). The recent update on the DNAS framework adds more components relevant to static attributes of building occupants (Chandra-Putra et al, 2021).…”

Section: Occupant Data Ontologymentioning

confidence: 99%

Generating synthetic occupants for use in building performance simulation

Putra

Andrews

Hong

2021

Journal of Building Performance Simulation

View full text Add to dashboard Cite

Occupant behavior simulation frameworks can employ synthetic populations to characterize occupancy and behavioral patterns in buildings based on real demographic data at a certain geographical location. Multiple methods are available to generate a synthetic population, with pros-and cons-for different applications and contexts. For buildings, very few synthetic occupant populations have been generated. This paper uses a Bayesian Networks (BN) structural learning approach to synthesize populations of occupants in a multi-family housing. Two additional cases of office occupants and senior housing residents are considered as a cross-case comparison. We draw upon the extended version of Drivers-Needs-Actions-Systems (DNAS) framework to guide the selection of variables and data imputation. The resulting synthetic occupant data is evaluated by comparing the joint distributions between the actual and synthetic data sets, % difference, and Standardized-Root-Mean-Squared-Error (SRMSE). Our results show that the BN approach is powerful in learning the structure of data sets. The synthetic data sets successfully match the joint distributions of the underlying combined data sets. Experiments on the multi-family housing particularly show the best performance compared to the cases of office and senior housing. Future work includes testing and demonstration of how the synthetic data sets feed to occupant behavior module through co-simulation with building performance simulation tools, such as EnergyPlus.

show abstract

Summertime thermal conditions and senior resident behaviors in public housing: A case study in Elizabeth, NJ, USA

Cited by 27 publications

References 53 publications

Thermally resilient communities: creating a socio-technical collaborative response to extreme temperatures

Thermally resilient communities: creating a socio-technical collaborative response to extreme temperatures

An ontology to represent synthetic building occupant characteristics and behavior

Generating synthetic occupants for use in building performance simulation

Contact Info

Product

Resources

About