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The presentation provides a summary of objectives and current status of NASA Small Spacecraft Technology program's investment in laser communications technology.
Milwaukee County has experienced an increase in flooding due to climate change and urbanization. The frequency and severity of flooding vary spatially due to differences in land cover, surface permeability, and infrastructure. Marginalized communities tend to experience disproportionately high flooding and damage due to infrastructural inequalities and limited access to resources. To quantify these differences, we used the Natural Capital Project’s Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) Urban Flood Risk Mitigation Model to calculate and create maps of runoff retention, nominal flood depth, and economic damage to buildings in Milwaukee. Our model inputs included land cover, surface permeability, and rainfall. To inform our precipitation inputs, we used NASA’s Integrated Multi-satellite Retrievals for Global Precipitation Measurement (GPM IMERG) and National Weather Service (NWS) data. We assessed the relationship between flood risk and social and environmental spatial data including redlining, racial demographics, greenspace, and community resilience. The data demonstrate that flood risk is higher in historically redlined neighborhoods, majority Hispanic and Black census block groups, areas that lack parks and trees, and areas of low community resilience as measured by the Census Bureau’s Community Resilience Estimates (CRE). These findings will support our partners, Groundwork Milwaukee and Groundwork USA, in their efforts to promote the equitable distribution of resources and support environmental health in urban spaces. The end products of this project provide our partners with tools to assess urban flooding vulnerability, guide future intervention projects, quantify the effects of environmental injustice, and improve stakeholder access to data.
Long-term Objective: - Enable on-orbit high-accuracy absolute calibration for the past, current, and future reflected solar sensors in LEO and GEO by providing lunar spectral irradiance as function of satellite viewing geometry and specified wavelength. IIP Objective (complete): - Design, build, and characterize a prototype instrument demonstrating form-fit-function for a 6U CubeSat. InVEST Objective: - Demonstrate high-accuracy measurements of lunar spectral reflectance, < 0.5% (k=1), via 6U CubeSat on-orbit in LEO for 6 months, with validation and data analysis
The National Aeronautics and Space Administration’s (NASA) Astrophysics Division (APD) funds the development of cutting-edge technologies through multiple programs to enable its strategic missions to achieve ambitious and groundbreaking science goals. These technology development efforts are managed by the Cosmic Origins (COR), Exoplanet Exploration (ExE), and Physics of the Cosmos (PhysCOS) programs. The 2020 Astronomy and Astrophysics Decadal Survey, “Pathways to Discovery in Astronomy and Astrophysics for the 2020s,” (Astro2020) recommended a pan-chromatic set of missions, including three Great Observatories (GO) and three Probe-class missions that could collect unprecedented data over the coming decades. We show the correlation between these strategic missions and the current Astrophysics technology gaps, as well as recent and current technology maturation projects funded to help close these technology gaps. We also cover how these investments advanced their Technology Readiness Levels (TRLs) [1] and where they have been infused into missions and projects.
Dollars saved through energy efficiency can directly impact your bottom line. Whether you are planning for a major renovation or upgrading individual pieces of building equipment, these improvements can help reduce operating costs, save on utility bills, and boost profits. This fact sheet provides guidelines for SBA lenders to understand the value of financing energy efficiency investments.
Presentation by Senior Engineer John Gonzales on Evaluating Investments in Natural Gas Vehicles and Infrastructure for Your Fleet using the Vehicle Infrastructure Cash-flow Estimation (VICE) 2.0 model.
The American Recovery and Reinvestment Act stimulus funding of 2009 for smart grid projects resulted in the tripling of smart meters deployment. In 2012, the Green Button initiative provided utility customers with access to their real-time1 energy usage. The availability of finely granular data provides an enormous potential for energy data analytics and energy benchmarking. The sheer volume of time-series utility data from a large number of buildings also poses challenges in data collection, quality control, and database management for rigorous and meaningful analyses. In this paper, we will describe a building portfolio-level data analytics tool for operational optimization, business investment and policy assessment using 15-minute to monthly intervals utility data. The analytics tool is developed on top of the U.S. Department of Energy’s Standard Energy Efficiency Data (SEED) platform, an open source software application that manages energy performance data of large groups of buildings. To support the significantly large volume of granular interval data, we integrated a parallel time-series database to the existing relational database. The time-series database improves on the current utility data input, focusing on real-time data collection, storage, analytics and data quality control. The fully integrated data platform supports APIs for utility apps development by third party software developers. These apps will provide actionable intelligence for building owners and facilities managers. Unlike a commercial system, this platform is an open source platform funded by the U.S. Government, accessible to the public, researchers and other developers, to support initiatives in reducing building energy consumption.
Commercial mortgages currently do not fully account for energy factors in underwriting and valuation, particularly as it relates to the impact of energy costs and volatility on an owner’s net operating income. As a consequence, energy efficiency is not properly valued and energy risks are not properly assessed and mitigated. Commercial mortgages are a large lever and could be a significant channel for scaling energy efficiency investments. A pilot analysis of loans with different mortgage contract structures and locations showed that when energy cost volatility was included in mortgage valuation, a 20% reduction in energy use resulted in a 1.3% average increase in mortgage value. This suggests that the explicit inclusion of energy use and volatility in mortgage valuation can send a strong price signal that financially rewards and values energy efficiency in commercial properties. This paper presents findings from a scoping study addressing energy factors in commercial mortgages. First, we present a review of current practices as it relates to incorporating energy factors into commercial mortgage underwriting and valuation. Next, we detail the impacts of energy factors on property values, net operating income and mortgage valuation. Building operational practices alone can result in energy use variations from -17% to 87%. Finally, we present a set of proposed interventions to properly address energy factors in commercial mortgages, based on extensive discussions with stakeholders including mortgage originators, underwriters, building owners and regulators.
This paper presents new results on the link between energy factors and commercial mortgage default. First, we summarize results from an empirical analysis of the impact of source energy use intensity (EUI) and electricity prices on mortgage default. We used a unique data set that merges building-level energy use data from city benchmarking ordinances and financial data for commercial mortgages on the same buildings. We found that building source EUI and electricity price are statistically and economically associated with commercial mortgage defaults. Next, we present five case studies on the impact of energy use and price variations on default risk: three office buildings, a hotel, and a multi-family residential building. We use the empirical model coefficients to compute the default risk impacts due to variations in source EUI and electricity price over the course of the mortgage term. We found that variations in source EUI could raise or lower the default rates in these properties by between 5% and 40%, depending on the property type and geography. Electricity pricing has an even greater effect – roughly 60% change in default rate in the Denver area and nearly 90% in northern California. Finally, we propose an energy risk score that lenders can use to assess energy risk and inform mortgage terms. The score is being developed and piloted in collaboration with three mortgage lenders. We conclude with implications of this score as a market signal and mechanism for incentivizing energy efficiency investments through the commercial mortgage channel.
Collaboration between the DHS Cybersecurity and Infrastructure Security Agency (CISA) and public- sector partners has revealed that a dearth of cyber- incident data combined with the unpredictability of cyber attacks have contributed to a shortfall in first-party cyber insurance protection in the critical infrastructure community. This research explores the foundations of insurance theory and adopts behavioral manipulation methods to incentivize cyber-security investment. We validate the model by applying power industry performance data from 2013-2015 to assess risk facing the industry. Results show that the model can successfully discriminate between individual power companies as well as geographic regions on the basis of risk and can recommend cyber risk- management strategies tailored to individual risk profiles. Here, the adoption of this framework could invite more market participation, which will create a more robust cyber- incident reporting environment, contributing directly to the DHS goal of creating a national cyber- incident data repository.
NREL analysis will inform VTO on costs/benefits of DOE investment in an array of electric vehicle charging infrastructure technologies, trade-offs between residential and non-residential solutions, and cost of charging to consumers. Additional analysis will focus on vehicle sales, energy consumption, and emission impacts of meeting DOE technology target goals ahead of or behind schedule (timing assessment).
Environmentally acceptable lubricants (EALs) are defined as lubricants that meet U.S. Environmental Protection Agency (EPA) standards for “biodegradability, toxicity, and bioaccumulation potential that minimize their likely adverse consequences in the aquatic environment, compared to conventional lubricants.” Restrictions from state, local, and federal agencies, as well as a growing awareness of the environmental risks associated with petroleumbased lubricants, have shifted government and industry to seek out high-performing EALs. The U.S. Department of Energy (DOE) is working to reduce the environmental impacts of hydropower development and operation by investing in tools and methods to develop, demonstrate, and validate EAL materials.
This guide provides an overview of the federal investment tax credit for those interested in commercial solar photovoltaics, or PV.
Renewable energy development can bolster local economies through job creation, local tax revenues, and reduced energy costs; however, communities most in need of economic development and employment opportunities often see lower levels of renewable energy deployment. We sought to identify areas where indicators of disadvantaged communities intersect with high generation potential from cost- effective renewable energy opportunities. This presentation highlights the geospatial intersection of the technical potential and levelized cost of energy for three renewable technologies (residential solar, utility solar, and land-based wind) and three sociodemographic metrics (energy burden, unemployment, and employment in mining, quarrying, and oil and gas extraction). This research and the associated county-level data set are intended to inform national- and state-level energy-related assistance programs, economic development efforts, and infrastructure programs seeking to prioritize investments in disadvantaged communities.
Disclosed herein are embodiments of a coating composition for use in investment casting. The coating composition embodiments provide a solidified coat that can be as a mold for casting castable materials and that is easily removed from the casted material using water. The coating composition embodiments disclosed herein are reusable and are non-toxic and exhibit high thermal stability.
Energy efficiency is a key demand-side strategy for sustainability, recently identified by the United States Department of Energy as a pillar of industrial decarbonization. The increased focus on decarbonization and the requirement for efficiency to enable electrification, another decarbonization pillar, due to the spark spread between natural gas and electricity prices, make energy efficiency increasingly relevant. Still, industries face challenges in adopting energy efficiency measures. Researchers have long found a gap in adoption of even those measures with a profitable net present value, attributed to lack of strategic value among other barriers (see for rigorous exploration and taxonomy). One solution to facilitate energy efficiency projects is the inclusion of non-energy impacts, as this has been shown to double potential deployment of such projects at system level. Energy efficiency can provide valuable benefits outside of simple operating cost reductions, from decreased pollution to enhanced productivity. The inclusion of these benefits in decision making assessments faces hurdles due to inconsistency of ancillary benefits across projects, difficulties in quantifying impacts and the need for additional measurement to quantify them. The decision-making tools to support this have been designed primarily for the European context. We begin with a stakeholder engagement process to better characterize the U.S. decision making process surrounding adoption of energy efficiency investments. Characterization of non-energy impacts has developed substantially over recent decades. Cagno et al. provided a framework for studying the applicability of these impacts to energy efficiency projects, listing 120 key performance indicators focused mainly on reductions of costs/harms. Other researchers have included impacts on the strategic and revenue side that can be merged into this framework as well. We seek a tractable set of impacts that can be included in a decision-making tool in the US, and as such are well suited to US industry, management and decision making processes. We also seek to understand how to best quantify or characterize these impacts. This work will demonstrate the results of a survey conducted among US manufacturing industry decision makers to assess the decision making landscape of stakeholders as well as the most relevant performance indicators for energy efficiency projects.
Highlights: • An integrated burden of transportation in association with planned modifications of the public transit infrastructure. • Based on our results planned public transit projects in Montreal will not reduce significantly the burden of transportation. • Future work needs to address land use and public transit projects needed to further reduce the burden of transportation. Since public transit infrastructure affects road traffic volumes and influences transportation mode choice, which in turn impacts health, it is important to estimate the alteration of the health burden linked with transit policies.
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