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At least 19 records

Climate Change Potential Impacts on the Built Environment and Possible Adaptation Strategies

The built environment consists of components that exist at a range of scales from small (e.g., houses, shopping malls) to large (e.g., transportation networks) to highly modified landscapes such as cities. Thus, the impacts of climate change on the built environment may have a multitude of effects on humans and the land. The impact of climate change may be exacerbated by the interaction of different events that singly may be minor, but together may have a synergistic set of impacts that are significant. Also, mechanisms may exist wherein the built environment, particularly in the form of cities, may affect weather and the climate on local and regional scales. Hence, a city may be able to cope with prolonged heat waves, but if this is combined with severe drought, the overall result could be significant or even catastrophic, as accelerating demand for energy to cooling taxes water supplies needed both for energy supply and municipal water needs. This presentation surveys potential climate change impacts on the built environment from the perspective of the National Climate Assessment, and explores adaptation measures that can be employed to mitigate these impacts.

Quattrochi, Dale A.

Multi-criteria thermal resilience certification scheme for indoor built environments during heat waves

With climate change, the indoor built environment is expected to significantly influence the occupant's safety and well-being. A novel multi-criteria thermal resilience certification scheme for indoor built environments during extreme heat events is proposed in this paper. The certification scheme considers overheating, thermal comfort, heat stress, and hygrothermal discomfort in built environments. These criteria are quantified using key performance indicators like indoor overheating degree, hours of exceedance, wet-bulb globe temperature, and heat index, respectively. This scheme is developed based on existing best practices like standards, rating systems, and literature. The scheme is implemented on a benchmark building energy performance model for detached post-World War II dwellings in Belgium as a case study using weather data measured from the City of Brussels. The indoor overheating in the reference dwelling is assessed with a static threshold of 27 °C for the bedrooms and adaptive thresholds for other areas. The analysis found that the building performance is within the defined threshold levels throughout the heat wave duration for all criteria. Therefore, the reference dwelling got a maximum attainable score of four points and is rated five-star for thermal resilience during heat waves. The proposed certification scheme is intended as a standardized framework and highlights the need for further revisions in building performance policies and guidelines.

Climate change

Scenario Generation for Built Environment Decision Support under Uncertainty: Case Studies of Airflow Modeling and Climate-Resilient Infrastructure System Design

When confronted with unforeseen challenges, practicing informed decision making is crucial for enhancing resilience in the built environment. While scan-to-building information modeling (BIM) is a well-established approach for creating detailed digital representations of physical assets, its application in assessing and improving infrastructure resilience remains underexplored. This study addresses this gap by proposing a novel application of scan-to-BIM, namely, scan-to-BIM-to-digital twin (S-BIM-DT) workflow. By integrating reality capture and digital twin technologies, this workflow creates continuously updated and accurate digital representations of physical assets, enabling the generation of various scenarios. Unlike traditional methods, the S BIM-DT workflow facilitates continuous model refinement, supporting informed resilience strategies. By combining these technologies into a cohesive process, the workflow facilitates decision making under uncertainty, enabling stakeholders to evaluate and respond to various scenarios effectively. We demonstrate the implementation of the S-BIM-DT workflow through two use cases that highlight its capability to enhance resilience at different scales. The first use case involves the Combined Transportation, Emergency, and Communications Center (CTECC) in Austin, Texas. BIM-enriched computational fluid dynamics (CFD) modeling simulates airflow and develops alternative scenarios for optimizing the heating, ventilation, and air conditioning (HVAC) systems. This approach enhances resilience against airborne health threats in a postCOVID context. The second use case focuses on designated areas within Beaumont, Texas, as part of the Southeast Texas Urban Integrated Field Laboratory (SETx-UIFL) research. By developing inundation maps to assess extreme weather events, this modeling aids in preparedness efforts and informs the development of climate-resilient infrastructure in vulnerable neighborhoods. Results indicate that the S-BIM-DT workflow effectively generates scenarios that enhance resilience in the built environment by facilitating informed decision making. Furthermore, this study serves as a bridge between advanced scan-to-BIM methodologies and the practical strategies needed to improve built infrastructure resilience.

Built environment

A Novel Framework for Performance Evaluation and Design Optimization of PCM Embedded Heat Exchangers for the Built Environment

This research sheds light on the performance evaluation and design optimization of PCM-HXs for the built environment, addressing several barriers to practical issues to PCM-HX commercialization such as modeling aspects (i.e., modeling expertise and computational / time investment, etc.), manufacturing aspects (i.e., at-scale manufacturing, cost assessments, etc.) and experimental performance assessment (i.e., reliable experimental data, assessment of multiple PCM-working fluid combinations, etc.). We present a novel, comprehensive, and experimentally-validated design optimization framework for PCM-HXs capable of simulating any PCM-HX geometry with reasonable accuracy and significant computational time savings when compared to traditional CFD-based design practices. The framework was validated for a wide range of PCM-HX configurations, including a design optimization for a domestic hot water heater application where TES partially replaces electrical heating input. The resulting PCM-HXs were found to deliver 34-68% of the total daily hot water supply with only 5-10% package volume increase from the water heater, thus within U.S. DOE targets for TES systems. To identify the most promising HXs for PCM applications, first-order geometry and cost analyses were conducted based on off-the-shelf HX products. As part of this work, 9 PCM-HX prototypes were manufactured using additive and conventional manufacturing methods. Detailed economy-of-scale assessments were conducted for the most promising PCM-HXs and were found to have a good outlook for the next 5-10 years. The PCM-HX design optimization framework was validated through comprehensive in-house experimental testing using newly-developed PCM-to-fluid test facilities. In total,10 total in-house component-level experiments were conducted using these prototypes, including 9 with water and 1 with refrigerant (R410A) as the working fluid. It was found that the framework can successfully predict experimental thermal-hydraulic performance within ±10-20% the first time without manual design changes, eliminating the need for time-consuming and expensive prototyping efforts as part of the design process. As part of this work, a publicly-available PCM web tool was released which includes a PCM property database (531 PCMs) and PCM-HX modeling tool to assist the design community on common PCM-HX use-cases, e.g., single/multiple flow path(s) fluid-to-PCM and air-to-fluid-to-PCM configurations (https://ceeeweb.umd.edu/pcmapp/). This work will accelerate the design and time to market for next generation PCM-HXs.

25 ENERGY STORAGE

Air, surface, and wastewater surveillance of SARS-CoV-2; a multimodal evaluation of COVID-19 detection in a built environment

Environmental surveillance of infectious organisms holds tremendous promise to reduce human-to-human transmission in indoor spaces through early detection. In this study we determined the applicability and limitations of wastewater, indoor high-touch surfaces, in-room air, and rooftop exhaust air sampling methods for detecting SARS-CoV-2 in a real world building occupied by residents recently diagnosed with COVID-19. We concurrently examined the results of three 24-hour environmental surveillance techniques, indoor surface sampling, exhaust air sampling and wastewater surveillance, to the known daily census fluctuations in a COVID-19 isolation dormitory. Additionally, we assessed the ability of aerosol samplers placed in the large volume lobby to detect SARS-CoV-2 multiple times per day. Our research reveals an increase in the number of individuals confirmed positive with COVID-19 as well as their estimated human viral load to be associated with statistically significant increases in viral loads detected in rooftop exhaust aerosol samples (p = 0.0413), wastewater samples (p = 0.0323,), and indoor high-touch surfaces (p < 0.001)). We also report that the viral load detected in lobby aerosol samples was statistically higher in samples collected during presence of occupants whose COVID-19 diagnostic tests were confirmed positive via qPCR compared to periods when the lobby was occupied by either contact-traced (suspected positive) individuals or during unoccupied periods (p = 0.0314 and <2e–16). We conclude that each daily (24h) surveillance method, rooftop exhaust air, indoor high-touch surfaces, and wastewater, provide useful detection signals for building owner/operator(s). Furthermore, we demonstrate that exhaust air sampling can provide spatially resolved signals based upon ventilation exhaust zones. Additionally, we find that indoor lobby air sampling can provide temporally resolved signals useful during short duration sampling periods (e.g., 2-4 hours) even with intermittent occupancy by occupants diagnosed with COVID-19.

60 APPLIED LIFE SCIENCES

An Analysis of the Spatial Variations in the Relationship Between Built Environment and Severe Crashes

Traffic crashes significantly contribute to global fatalities, particularly in urban areas, highlighting the need to evaluate the relationship between urban environments and traffic safety. This study extends former spatial modeling frameworks by drawing paths between global models, including spatial lag (SLM), and spatial error (SEM), and local models, including geographically weighted regression (GWR), multi-scale geographically weighted regression (MGWR), and multi-scale geographically weighted regression with spatially lagged dependent variable (MGWRL). Utilizing the proposed framework, this study analyzes severe traffic crashes in relation to urban built environments using various spatial regression models within Leon County, Florida. According to the results, SLM outperforms OLS, SEM, and GWR models. Local models with lagged dependent variables outperform both the global and generic versions of the local models in all performance measures, whereas MGWR and MGWRL outperform GWR and GWRL. Local models performed better than global models, showing spatial non-stationarity; so, the relationship between the dependent and independent variables varies over space. The better performance of models with lagged dependent variables signifies that the spatial distribution of severe crashes is correlated. Finally, the better performance of multi-scale local models than classical local models indicates varying influences of independent variables with different bandwidths. According to the MGWRL model, census block groups close to the urban area with higher population, higher education level, and lower car ownership rates have lower crash rates. On the contrary, motor vehicle percentage for commuting is found to have a negative association with severe crash rate, which suggests the locality of the mentioned associations.

Alisan, Onur (ORCID:0000000193113984)

Dynamic Accounting of Carbon Uptake in the Built Environment

Transforming building materials from net life-cycle CO 2 e emitters to carbon sinks is a key pathway towards decarbonizing the industrial sector. Current life-cycle assessments of materials (particularly “low-carbon” materials) often focus on cradle-to-gate emissions, which can exclude emissions and uptake (i.e., fluxes) later in the materials’ life-cycle. Further, conventional CO 2 e emission characterization disregards the dynamic effects of the timing of emissions and uptake on cumulative radiative forcing from processes like manufacturing, biomass growth, and the decadal carbon storage in long-lived building materials. This work presents a framework to analyze the cradle-to-grave CO 2 e balance of building materials using a time-dependent global warming potential calculation. We apply this framework in the dynamic accounting of carbon uptake in the built environment (D-CUBE) tool and examine two case studies: concrete and cross-laminated timber (CLT). When accounting for dynamic effects, the long storage time of biogenic carbon in CLT results in reduced warming, while the slow rate of uptake via concrete carbonation does not result in significant reductions in global warming. The D-CUBE tool allows for consistent comparisons across materials and emissions mitigation strategies at varying life-cycle stages and can be adapted to other materials or systems with different lifespans and applications. The flexibility of D-CUBE and the ability to identify CO 2 e emission hot-spot life-cycle stages will be instrumental in identifying pathways to achieving net-carbon-sequestering building materials.

54 ENVIRONMENTAL SCIENCES

Climate Change Impacts on the Built Environment in the United States and Implications for Sustainability

As an integral part of the National Climate Assessment (NCA), technical assessment reports for 13 regions in the U.S. that describe the scientific rationale to support climate change impacts within the purview of these regions, and provide adaptation or mitigation measures in response to these impacts. These technical assessments focus on climate change impacts on sectors that are important environmental, biophysical, and social and economic aspects of sustainability within the U.S.: Climate change science, Ecosystems and biodiversity, Water resources, Human health, Energy supply and use, Water/energy/land use, Transportation, Urban/infrastructure/vulnerability, Agriculture, Impacts of climate change on tribal/indigenous and native lands and resources, Forestry, Land use/land cover change, Rural communities development, and Impacts on biogeochemical cycles, with implications for ecosystems and biodiversity. There is a critical and timely need for the development of mitigation and adaptation strategies in response to climate change by the policy and decision making communities, to insure resiliency and sustainability of the built environment in the future.

Quattrochi, Dale A.

Sensor Placement Optimization Study for the Built Environment: Operational Use Cases

Systems of fixed-position radiation sensors can provide information that assists emergency responders following nuclear and radiological incidents. State, local, tribal, and territorial (SLTT) government agencies that implement systems of fixed-position sensors are faced with numerous decisions regarding sensor selection, quantity, and placement. To develop guidance on implementation of radiation detection systems, we simulated the release of radioactive material in an urban environment using a combination of three models: the Weather Research Forecasting (WRF), Quick Urban and Industrial Complex (QUIC), and Monte Carlo N-Particle (MCNP) models. We then evaluated the performance of several hypothetical sensor systems. The small number of simulations we conducted are not sufficient to generate definitive design guidance for radiation sensor systems, but we did identify trends that would be of interest to emergency planners. For a scenario that releases 1000 curies of Cs-137, radiation detectors were needed at 500-meter intervals to have a high likelihood of event detection and to estimate source location and plume detection. We also noted that optimal detector altitude varied with distance to the source. We recommend additional research in this area be conducted to support developing sensor placement guidelines that expand on a range of locations, isotopes, activity levels, and different weather conditions. Original simulation strategies included a range of environments, additional radioisotopes (Am241 and AmBe), and a larger selection of sensor types. These types of expansions would support SLTT guidance on sensor system recommendations.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND

Sensor Placement Optimization Study for the Built Environment: Next Steps Report

Systems of fixed-position radiation sensors can provide information that assists emergency responders following nuclear incidents. First responder organizations that implement systems of fixed-position sensors face numerous decisions regarding sensor selection, quantity, and placement. Researchers at Pacific Northwest National Laboratory (PNNL) have evaluated the performance of several hypothetical sensor systems during a simulated activation of a radiological dispersal device. Due to technical limitations, PNNL’s analysis was limited to a single location and number of scenarios. This document describes additional research and analysis that would result in improved guidance to first responder organizations considering installation of radiation monitoring systems.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND

Urban forms, physical activity and body mass index: a cross-city examination using ISS Earth Observation photographs

Johnson Space Center has archived thousands of astronauts acquired Earth images. Some spectacular images have been widely used in news media and in k-12 class room, but their potential utilizations in health promotion and disease prevention have relatively untapped. The project uses daytime ISS photographs to define city forms and links them to city or metropolitan level health data in a multicity context. Road connectivity, landuse mix and Shannon's information indices were used in the classification of photographs. In contrast to previous remote-sensing studies, which tend to focus on a single city or a portion of a city, this project utilized photographs of 39 U.S. cities. And in contrast to previous health-promotion studies on the built environment, which tend to rely on survey respondents' responses to evaluate road connectivity or mixed land use for a single study site, the project examined the built environments of multiple cities based on ISS photos. It was found that road connectivity and landuse mix were not statistically significant by themselves, but the composite measure of the Shannon index was significantly associated with physical activity, but not BMI. Consequently, leisure-time physical activity seems to be positively associated with the urban complexity scale. It was also concluded that unless they are planned or designed in advance, photographs taken by astronauts generally are not appropriate for a study of a single-site built environment nor are they appropriate for a study of infectious diseases at a local scale. To link urban built environment with city-wide health indicators, both the traditional nadir view and oblique views should be emphasized in future astronauts' earth observation photographs.

Lin, Ge

A Novel Machine Learning Workflow to Classify Mobile Home Parks at Scale

Understanding the built environment is essential to the overall study of population dynamics, grid infrastructure, emergency response, among others. In the United States there are multiple classifications for buildings within the built environment such as residential, signifying family homes while commercial buildings consist of apartments or larger structures which are multi-purpose. While there is a high level of understanding of where these aforementioned structures are located, there is a third class of structures, mobile home parks (MHP) which have been under-represented in the literature despite there being an estimated 2.7 million of them within the United States. Research has shown that individuals who reside in MHP are at higher risk to extreme events due to their location and structural integrity of residence. Attention must now turn to identifying MHP at scale to help first responders and policy makers understand where these at risk populations reside. To address for this gap, we develop a novel methodology to infer MHP at scale based off morphologies derived at a building level. Here, we show that across 3 million buildings in 6 states within the United States it is possible to identify MHP with 83% accuracy. This novel approach to identify MHP from other structures within the built environment using a machine learning approach provides a new tool to leverage in relation to helping at-risk populations.

Stipek, Clinton [Oak Ridge National Laboratory (OR

The Urban Environmental Monitoring/100 Cities Project: Legacy of the First Phase and Next Steps

The Urban Environmental Monitoring (UEM) project, now known as the 100 Cities Project, at Arizona State University (ASU) is a baseline effort to collect and analyze remotely sensed data for 100 urban centers worldwide. Our overarching goal is to use remote sensing technology to better understand the consequences of rapid urbanization through advanced biophysical measurements, classification methods, and modeling, which can then be used to inform public policy and planning. Urbanization represents one of the most significant alterations that humankind has made to the surface of the earth. In the early 20th century, there were less than 20 cities in the world with populations exceeding 1 million; today, there are more than 400. The consequences of urbanization include the transformation of land surfaces from undisturbed natural environments to land that supports different forms of human activity, including agriculture, residential, commercial, industrial, and infrastructure such as roads and other types of transportation. Each of these land transformations has impacted, to varying degrees, the local climatology, hydrology, geology, and biota that predate human settlement. It is essential that we document, to the best of our ability, the nature of land transformations and the consequences to the existing environment. The focus in the UEM project since its inception has been on rapid urbanization. Rapid urbanization is occurring in hundreds of cities worldwide as population increases and people migrate from rural communities to urban centers in search of employment and a better quality of life. The unintended consequences of rapid urbanization have the potential to cause serious harm to the environment, to human life, and to the resulting built environment because rapid development constrains and rushes decision making. Such rapid decision making can result in poor planning, ineffective policies, and decisions that harm the environment and the quality of human life. Slower, more thought-out, decision making could result in more favorable outcomes. The harm to the environment includes poor air quality, soil erosion, polluted rivers and aquifers, and loss of wildlife habitat. Human life is then threatened because of increased potential for disease spreading, human conflict, environmental hazards, and diminished quality of life. The built environment is potentially threatened when cities are built in areas that can be impacted by events such as hurricanes, tsunamis, earthquakes, fires, and landslides. Our goals include assessing the threat of such events on cities and the people living there.

Stefanov, William L.