Ambient population as a composition of explicit built-environment supports
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97 MATHEMATICS AND COMPUTING↗
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Analogs for Microbiome of the Built Environment and Planetary Protection
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Parag Vaishampayan↗
Microbes from the International Space Station Built Environment
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Aubrie O'Rourke↗
Microbial Burden Estimation of Food Items, Built Environments, and the International Space Station Using Film Media
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Anna C. Simpson↗
Valuing Energy Efficiency and Distributed Energy Resources in the Built Environment: Preprint
Traditionally, analytical frameworks that underpin building energy policy have focused on the need to reduce annual energy consumption by assessing the cost and efficiency performance of energy-consuming technologies. Investments in distributed energy resources (DERs) such as photovoltaics have generally been evaluated independently, but also on a cost and performance basis. However, buildings are rapidly evolving to incorporate technologies that not just consume energy, but also generate, store, and control energy loads. Concurrently, the electric grid is becoming more dynamic and variable due to the increased proportion electricity production from variable renewable sources. To that end, building energy policy analytical frameworks should be updated to include the interactions between energy efficiency and DERs as well as potential value streams for the grid and building owner that technologies or packages of technologies might offer. As buildings with DERs and controllable loads are able to provide grid services or optimize operations based on electricity rates and grid conditions, the temporal and spatial nature of these technologies should also be incorporated into design decisions. To explore these questions further, the National Renewable Energy Laboratory will use a series of building and electric grid models to simulate the design and operation of a neighborhood of buildings under various electricity rates, grid conditions, and potential compensation scenarios. Scenarios of time-sensitive values for future grid services will also be constructed for use in the analysis. New metrics that can be used in building energy policies will also be explored to capture the responsiveness or flexibility of high efficiency buildings with DERs under various electric grid conditions and future scenarios.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
Valuing Energy Efficiency and Distributed Energy Resources in the Built Environment
Traditionally, analytical frameworks that underpin building energy policy have focused on the need to reduce annual energy consumption by assessing the cost and efficiency performance of energy-consuming technologies. Investments in distributed energy resources (DERs) such as photovoltaics have generally been evaluated independently, but also on a cost and performance basis. However, buildings are rapidly evolving to incorporate technologies that not just consume energy, but also generate, store, and control energy loads. Concurrently, the electric grid is becoming more dynamic and variable due to the increased proportion electricity production from variable renewable sources. To that end, building energy policy analytical frameworks should be updated to include the interactions between energy efficiency and DERs as well as potential value streams for the grid and building owner that technologies or packages of technologies might offer. As buildings with DERs and controllable loads are able to provide grid services or optimize operations based on electricity rates and grid conditions, the temporal and spatial nature of these technologies should also be incorporated into design decisions. To explore these questions further, the National Renewable Energy Laboratory will use a series of building and electric grid models to simulate the design and operation of a neighborhood of buildings under various electricity rates, grid conditions, and potential compensation scenarios. Scenarios of time-sensitive values for future grid services will also be constructed for use in the analysis. New metrics that can be used in building energy policies will also be explored to capture the responsiveness or flexibility of high efficiency buildings with DERs under various electric grid conditions and future scenarios.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Metrics and Analytical Frameworks for Valuing Energy Efficiency and Distributed Energy Resources in the Built Environment: Preprint
This paper summarizes efforts to develop new—and enhance existing—analytical frameworks and metrics to quantify the value that grid-interactive efficient homes with solar (GEB-solar homes) can provide. Industry is working to characterize and understand these capabilities and benefits, but existing analytical frameworks for evaluating energy efficiency (EE) are often siloed from those that evaluate distributed energy resources (DERs). Five metrics were adapted from an extensive literature review and applied to case studies of a modeled home in Riverside, California: ramp up/down, cover factor demand/supply, and curtailable load. Eight different technology scenarios were analyzed using a more tightly connected suite of building-to-grid models (BEopt, REopt, ReEDS, and PLEXOS). Additionally, an initial version of the Cambium tool was developed, characterizing the marginal prices and emissions from NREL’s 2018 Standard Scenarios. These grid costs were extended to a time-varying proxy retail rate and applied as part of a new grid alignment metric. In the results, a more integrated combination of GEB-solar technologies led to a higher cover factor demand—the percentage of gross home load covered by on-site solar—however, a benchmark was required to determine what range of cover factor was “best” for given grid conditions. To that end, a grid alignment cost metric was applied to the case study scenarios. The average cost to serve the net load of the home decreased from a median of ~$0.24/kWh to ~$0.10/kWh when the most integrated technology scenario was optimized towards the grid pricing proxy versus the time-of-use (TOU) rate.
41 EE - Solar Energy Technologies Office (EE-4S)↗
Developing micro-level urban ecosystem indicators for sustainability assessment
Sustainability assessment is increasingly being viewed as an important tool to aid in the shift towards sustainable urban ecosystems. An urban ecosystem is a dynamic system and requires regular monitoring and assessment through a set of relevant indicators. An indicator is a parameter which provides information about the state of the environment by producing a quantitative value. Indicator-based sustainability assessment needs to be considered on all spatial scales to provide efficient information of urban ecosystem sustainability. The detailed data is necessary to assess environmental change in urban ecosystems at local scale and easily transfer this information to the national and global scales. This paper proposes a set of key micro-level urban ecosystem indicators for monitoring the sustainability of residential developments. The proposed indicator framework measures the sustainability performance of urban ecosystem in 3 main categories including: natural environment, built environment, and socio-economic environment which are made up of 9 sub-categories, consisting of 23 indicators. This paper also describes theoretical foundations for the selection of each indicator with reference to the literature [Turkish] Highlights: • As the impacts of environmental problems have multi-scale characteristics, sustainability assessment needs to be considered on all scales. • The detailed data is necessary to assess local environmental change in urban ecosystems to provide insights into the national and global scales. • This paper proposes a set of key micro-level urban ecosystem indicators for monitoring the sustainability of residential developments. • This paper also describes theoretical foundations for the selection of each indicator with reference to the literature.
54 ENVIRONMENTAL SCIENCES↗
A review of smart building sensing system for better indoor environment control
Here this paper aims to provide a systemic review of how indoor sensors influence in managing optimal energy saving, thermal comfort, visual comfort, and indoor air quality in the built environment. The optimal management of energy saving and occupant comfort plays a vital role in the built environment because the occupant's productivity and health are highly influenced by indoor environmental quality. In order to do this, there must be a functional sensing system that connects the environment variables (e.g., temperature) with building environmental control systems such as the heating, ventilation, and air-conditioning system. This paper starts with an overview of the importance of energy saving and occupant comfort in the built environment. It then discusses sensors and their importance in the built environment and reviews the different types of sensors, which explains them in terms of how they influence the indoor built environment and occupant productivity. The paper further explores the application of sensors in the built environment and analyzes this in terms of energy saving, thermal comfort, visual comfort, and indoor air quality. Following this, the data analysis is discussed in terms of data, information, and knowledge accrued from the sensors. Lastly, the paper discusses the future challenges for the improvement of building indoor environmental quality and energy saving by the application of sensors.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Dynamics of Water, Climate, and Infrastructure
Climate and its impacts on the natural environment, and on the ability of the natural environment to support population and the built environment, stands as a threat multiplier that impacts national and global security. The Water Intersections with Climate Systems Security (WICSS) Strategic Initiative is designed to improve understanding of water’s role in, among other topics, the connection of critical infrastructure to climate in light of competing national and global security interests (including transboundary issues and stability), and identifying research gaps aligned with Sandia, and Federal agency priorities. With this impetus in mind, the WICSS Strategic Initiative team conceptualized a causal loop diagram (CLD) of the relationship between and among climate, the natural environment, population, and the built environment, with an understanding that any such regionally focused system must have externalities that influence the system from beyond its’ control, and metrics for better understanding the consequences of the set of interactions. These are discussed in light of a series of worldviews that focus on portions of the overall systems relationship. The relationships are described and documented in detail. A set of reinforcing and balancing loops are then highlighted within the context of the model. Finally, forward-looking actions are highlighted to describe how this conceptual model can be turned into modeling to address multiple problems described under the purview of the Strategic Initiative.
54 ENVIRONMENTAL SCIENCES↗
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↗
Ten questions concerning future buildings beyond zero energy and carbon neutrality
Not Available
Wang, Na (ORCID:0000000267308662)↗
The effect of lighting environment on task performance in buildings – A review
The effects of indoor environmental conditions on human health, satisfaction, and performance have been the focal point of research for decades. This paper reviews and summarizes the impact of lighting environment on task performance, specifically for the built environment audience. Existing studies included a variety of performance tests on cognitive performance and perception, visual acuity and reaction, memory, reasoning, and labor productivity. Illuminance, luminance ratio and correlated color temperature were found to affect performance in different ways, reflecting the impact of experimental techniques, conditions, performance evaluation methods used and data analysis methods. These were reviewed and categorized, with discussion on limitations related to sample size, modeling approach, carryover effects and other factors affecting individual differences in performance, with recommendations for future improvement. Although no universal conclusions can be made, in general, task performance seems to improve with higher illuminances, contrast ratios in the range of 7–11:1 (while always making sure that glare will not occur in the space) and higher correlated color temperature, while spectral tuning in the red or blue wavelengths has also shown positive effects. To obtain more generic evidence, future studies should be more consistent in terms of experimental procedures and overall light conditions, and also consider the effects of vertical illuminance, daylight provision/control, and outside views on task performance. Finally, studying performance with multi-factorial designs in a human-centered optimized manner (such as deploying variable lighting scenarios optimized for various tasks) can lead to deeper understanding of lighting effects on task performance, and ultimately to improved lighting design and operation in buildings overall.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Scaling Automatic Vector Data Alignment to Satellite Imagery
Given the tremendous volume of accessible Earth Observation (EO) data, there is a need to develop scalable Geospatial Artificial Intelligence (GeoAI) solutions for time-sensitive applications. Scalability in this context refers to rapidly processing large-scale EO data using high performance computing resources. Accurate mapping of the built environment from remote sensing (RS) imagery has been one of the crucial components in GeoAI workflows for a wide spectrum of humanitarian applications. Derived vector data of built environment is often leveraged for disaster preparedness and response activities. However, factors such as differences in ortho-rectification, atmospheric conditions and human error, results in spatial misalignment between vector data and the timely available RS imagery. Model training for downstream tasks such as object detection, change analysis, etc., is negatively impacted due to such spatial misalignment. Although there has been progress towards automatic alignment of vector data, the lack of scalability remains an open research challenge. This paper proposes to leverage parallel computing to optimize an automatic vector data alignment workflow. It further employs CPU-level multi-core parallelism for improving the performance of the workflow for scalable built environment mapping. We report observations and discuss findings from the preliminary experiments performed on the Summit Supercomputer.
Potnis, Abhishek↗
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.↗
A segmented approach to modeling building height: Delineating high-rise and low-rise buildings for enhanced height estimation
Understanding building height is imperative to the overall study of energy efficiency, population distribution, urban morphologies, emergency response, among others. Currently, existing approaches for modeling building height at scale are hindered by two pervasive issues. First, there is no consistent approach to quantify what a high-rise building is at a macro scale, leaving researchers unable to accurately compare results across geographies and domains. Second, high-rise buildings represent a small fraction of the built environment, implying data imbalance challenges that negatively affect current approaches. This is a problem of practical relevance since information on high-rise buildings is important for studies on urban heat islands, population dynamics, and pollution dispersion. Here, we introduce a novel approach to map building height which first identifies two distinct distributions within the built environment, with one being composed of low-rise buildings and one composed of high-rise buildings. We then develop an ensemble scheme where discrete specialist models are trained for each subset of low-rise buildings and high-rise buildings to infer building height from morphology features. For experiments mapping heights of 4.85 million buildings in Japan, we show an increase of 34 % in accuracy within 3m error when compared to the current state-of-the-art when modeling high-rise buildings, which based on KNN experimentation we define as any building > 12m . Our findings show that such an ensemble framework outperforms the current state-of-the-art approaches, which is especially relevant in relation to inferring height for high-rise buildings, a prominent issue of existing approaches for mapping the built environment.
97 MATHEMATICS AND COMPUTING↗
Application of Whole Genome Sequencing and MALDI-TOF to the Identifcation of Bacillus Species Isolated from Cleanrooms at NASA Johnson Space Center
Astromaterial cleanrooms at NASA Johnson Space Center are built environments that hold samples, such as lunar rocks, from different space exploration missions. Bacillus sp. are frequently detected in routine microbial monitoring of these facilities. Since this, and related genera, can form endospores that can withstand harsh conditions, they could contaminate astromaterials. This could confound searches for extraterrestrial life. Whole genome sequencing (WGS) is widely used for identifying bacterial strains and tracking their source; however, WGS is expensive and time consuming. Matrix-assisted laser desorption ionization– time of flight mass spectrometry (MALDI-TOF) shows promise as a low-cost, rapid method of identifying strains of bacteria, but few studies have compared this proteomics method to WGS. To evaluate a high throughput method of tracking the source of contamination of this built environment, WGS and MALDI-TOF was conducted on 18 bacterial strains isolated from surfaces in astromaterials cleanrooms. WGS identified 14 Bacillus, 2 Paenibacillus, 1 Solibacillus and 1 Alcaligenes strains. These isolates showed similarity to strains commonly observed in spacecraft assembly cleanrooms at other facilities. Cluster analysis of mass spectra generated by MALDI-TOF grouped strains together that were greater than 94% similar to each other in terms of amino acid sequences of single copy core genes, as assessed by WGS. This suggests that MALDI-TOF and WGS results are consistent with each other and MALDI-TOF can rapidly identify strains of Bacillus sp. isolated from cleanroom environments with a resolution comparable to WGS. Based on phylogenomic analysis, these results also suggest the presence of a cosmopolitan class of Bacillus sp. that are more likely to be found in cleanrooms and similar built environments than in natural systems.
Farnaz Mazhari↗