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At least 829 records · Page 46

CROCUS Weather Data at Northwestern University Rooftop

This dataset is from the Department of Energy Office of Science funded project, Community Research on Urban and Climate Science (CROCUS) (https://crocus-urban.org/). Vaisala WXT sensor is an all-in-one weather instrument that provides 6 of the most important weather parameters: barometric pressure, temperature, relative humidity, rainfall, wind speed and direction. Temperature, pressure, relative humidity, and rainfall are sampled at 1 second frequency, while wind speed/direction is measured at ten per second (10Hz) frequency. These measurements are useful for looking at characterizing local weather, identifying unique weather events, and studying local turbulence, especially given the high temporal resolution of the wind measurements. Datasets are stored in the netCDF data format, and we we encourage users to make use the associated toolkits available from Unidata (https://www.unidata.ucar.edu/software/netcdf/), Project Pythia (https://foundations.projectpythia.org/core/data-formats/netcdf-cf.html), and our “Instrument Cookbooks” (https://crocus-urban.github.io/instrument-cookbooks) for more information on how to process the metadata-rich datasets.

EARTH SCIENCE > ATMOSPHERE > ATMOSPHERIC TEMPERATU↗

Wyandotte Integrated Renewable Energy Strategy (WIRES 2) (Final Technical Report)

Wyandotte Municipal Services (WMS), a Michigan Municipal Utility offering electric generation, transmission & distribution, water filtration & distribution and Broadband/Video sought to deploy a set of renewable energy projects for their Electric Utility that contributed to reducing the City’s environmental and energy impact, provided examples that would encourage businesses and citizens to adopt cleaner energy practices and help WMS meet the required renewable energy standards of the State of Michigan (10% in 2015, 15% in 2021). WMS generates and delivers roughly 280,000 megawatt hours (MWh) of electricity annually to more than 10,000 homes and 1,000 businesses within the City of Wyandotte. The Wyandotte Integrated Renewable Energy Strategy – WIRES 2 resulted in deployment of a set of community-scale micro-wind turbines, evaluation and installation of energy-efficient and low-maintenance light-emitting diode (LED) street lights and park lights in highly visible locations in the City and expansion of the geothermal heating and cooling district that already included residential geothermal systems, to include larger scale business/institutional systems at the Utility’s largest electric customer and at the City Library. Finally, WMS identified the need for job training in energy efficiency and renewable energy technologies to further develop a local skilled workforce in these areas. Partially funded by the grant, the wind turbine project provides a benchmark for WMS, local businesses and residents in the evaluation of utility-scale wind v. micro-wind in an urban environment as a renewable energy strategy. Also partially funded by the grant, the LED project benefited the City of Wyandotte by reducing load on the electric system for the public utility but also reduced City costs for streetlighting, parking lot lighting and park lighting without a compromise in security. The project also resulted in a visual success that has led to additional approvals for non-Grant related LED lighting installations resulting in further reduction in the electric load in the City. Commercial Geothermal installations resulted in the Utility being able to eliminate steam customers who formerly utilized the byproduct of steam from WMS electric production. Due to the reduction in natural gas prices and the overall reduction in market purchased power, it was no longer feasible for WMS to operate its Power Plant as a base load plant and to only operate on a market dispatch philosophy when market prices dictated that WMS could produce electricity cheaper than the market purchase price. This has resulted in fewer operating days for the WMS Power Plant, resulting in less environmental impact. WMS has now completely exited the steam business and the ability to offer a geothermal option to two (2) former steam customers (BASF-Wyandotte and the Bacon Memorial Library) allowed for that. In addition, peak loads have been shaved for these two (2) large customers due to the consistent temperature offered by geothermal heating and cooling, reducing the swings associated with thermostat changes caused by outside temperature changes during extreme high and low temperatures. Finally, energy efficiency and renewable energy college-level classes at Wayne County Community College allowed a group of interested students to pursue studies in those technologies through grant provided tuition, books and course materials. This effort provided a foundation of potential future employees not only for WMS but other energy efficiency/renewable energy employers such as Franklin Energy, a partner with WMS in energy optimization efforts with Wyandotte businesses.

17 WIND ENERGY↗

Computer Science Research Needs for Parallel Discrete Event Simulation (PDES)

Historically, scientific computing efforts have demonstrated the clear need for, and effective use of, supercomputing with traditional time-stepped simulations. Nevertheless, there are several areas in the mission spaces of the U.S. Department of Energy and other agencies waiting to tap advanced computing research using a different, discrete event style of modeling, simulation, and analysis. These span a wide spectrum of applications including energy grid resilience, urban planning and policy, transportation science, building technologies, emergency response and planning, environmental impact analysis, computational epidemiology, Internet communications, cyber security, and cyber-physical systems, to name only a few. Even within traditional scientific applications, the role of discrete event modes of execution is increasing in the form of new event-based mathematical solvers such as quantized state integration methods and discrete-continuous hybrid system solvers. Co-design of advanced supercomputing hardware systems is another area that exploits discrete event simulation at its core for effective analyses. Complex systems, entity behaviors and interconnections play a significant role in all these applications, which are mapped to large-scale models with discrete event formulations. To make advancements in all the aforementioned scientific areas, many technical aspects need to be more thoroughly studied and deeply understood in parallel discrete event simulation (PDES). The unique dynamics inherent in a discrete event modeling approach, by their very nature, intersect and influence the entire stack of the computing system, including (a) the unique nature of the instruction sets exercised in PDES workloads without a predominance of high-precision floating point operations, (b) virtual time-constrained multi-threaded execution of many logical processes per processor, (c) extremely variable and difficult to predict network traffic characteristics, (d) interfaces and inter-dependencies with machine learning and artificial intelligence codes at higher software layers, and (e) highly challenging load balancing needs, especially in effectively accounting for accelerated/extremely heterogeneous computing in current and future high-performance computing systems. Efficient and accurate parallel execution of PDES workloads is also dominated by challenges in dealing with their asynchronous concurrency fundamentally present at the model level. Conservative synchronization, optimistic/speculative synchronization, and their hybrid schemes open new questions in fundamental computer science with respect to reversibility of computation and prediction (lookahead) of behaviors inherent within model codes. On the implementation front, there are relatively few scalable, general-purpose parallel discrete event simulators in the world, and even fewer have been studied on emerging hardware platforms. To enable scientific advances using PDES, the research needs in computer science must also be pursued and met in the intersection of the algorithmic and hardware-aware aspects of scalable PDES engines. This report is aimed at capturing a computer science-oriented view of this important area of research in PDES, presenting a sample of important applications with their inherent discrete event technology elements. Needs are outlined in core areas of parallel discrete event research as well as cross-cutting directions in computer science research that positively impact scientific advancements across several important application areas. A selection of priority research opportunities in advanced computing for PDES is identified to serve as reference for key research topics and their order of importance for scientific advancements.

97 MATHEMATICS AND COMPUTING↗

Computer Science Research Needs for Parallel Discrete Event Simulation (PDES)

Historically, scientific computing efforts have demonstrated the clear need for, and effective use of, supercomputing with traditional time-stepped simulations. Nevertheless, there are several areas in the mission spaces of the U.S. Department of Energy and other agencies waiting to tap advanced computing research using a different, discrete event style of modeling, simulation, and analysis. These span a wide spectrum of applications including energy grid resilience, urban planning and policy, transportation science, building technologies, emergency response and planning, environmental impact analysis, computational epidemiology, Internet communications, cyber security, and cyber-physical systems, to name only a few. Even within traditional scientific applications, the role of discrete event modes of execution is increasing in the form of new event-based mathematical solvers such as quantized state integration methods and discrete-continuous hybrid system solvers. Co-design of advanced supercomputing hardware systems is another area that exploits discrete event simulation at its core for effective analyses. Complex systems, entity behaviors and interconnections play a significant role in all these applications, which are mapped to large-scale models with discrete event formulations.

97 MATHEMATICS AND COMPUTING↗

Handheld Raman Spectrometers: Assessment Report

In April 2022 the National Urban Security Technology Laboratory’s System Assessment and Validation for Emergency Responders program conducted an operational assessment of ten commercially available handheld Raman spectrometers. Additionally, prior to the operational assessment, the Pacific Northwest National Laboratory conducted laboratory testing of the devices, including scanning a number of samples in various containers. This report summarizes the results of the assessment.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Institutional and Policy Landscape for Solar-Plus-Storage Deployment by Electric Cooperatives

As co-location with battery storage has become a significant solar project-design trend across the United States, policies at all levels have started to adjust. Generally, these policies address battery storage development in major, urban markets, served by large investor-owned utilities (IOUs). Yet all kinds of utilities nationwide are seeking ways to tap into the fast-growing battery storage market, and they are all stakeholders in the federal, state, and local policies that impact the storage market's development. The electric cooperative sector, which includes some 830 distribution utilities and 63 generating and transmission (G&T) utilities across a mostly rural landscape, is no exception. It is impacted by federal, state, and local government policy requirements and incentives, as well as by policies that are controlled by the sector's own institutions. The objective of this paper is to identify and discuss the various policy and institutional factors that are relevant to the electric cooperative sector, and especially to local, distribution-level electric cooperatives (co-ops) that may be interested in procuring energy storage. Given this, the paper is largely written from the local co-op perspective. It also may be useful to wholesale G&T cooperatives. Other parties that may find the paper useful include storage developers, who are often unfamiliar with co-ops; local and state policymakers addressing policy options for this sector, and local renewable or storage stakeholders, who wish to understand the policy landscape affecting their local utility. Although co-op energy storage programs may tap customer-side batteries, this examination is focused on utility-side "front of the meter" projects and the policy issues they raise.

14 SOLAR ENERGY↗

Solar HBCU Innovation in Microgrids & Resiliency with Solar + Storage

The Breaking Barriers project was designed to improve electricity resilience at four Historically Black Colleges and Universities (HBCUs) in West Atlanta, as well as within the surrounding energy-burdened community. To do so, the project undertook work to design and construct innovative urban energy resiliency hubs integrating microgrid technology, solar generation, and energy storage in these West Atlanta colleges and communities. The hubs will help Atlanta HBCUs and the energy-burdened broader community be more resilient, in addition to informing new course curricula at Atlanta University Center campuses and inspiring similar efforts at other HBCUs and beyond.

14 SOLAR ENERGY↗

A formaldehyde and nitrogen dioxide toxics monitor for environmental justice

DOE’s Integrated Field Laboratories (IFLs) require a vast array of measurements to measure urban air quality. Nitrogen dioxide (NO2) and formaldehyde (HCHO) are ubiquitous pollutants with numerous sources, most notably vehicle exhaust. High-spatial density measurements are critical to understanding how certain neighborhoods are more adversely impacted by pollutants. This report describes the results of a Phase I SBIR project to develop and demonstrate a rapid, affordable, low-power monitor to provide high spatial resolution mobile measurements of formaldehyde and nitrogen dioxide at street-level, where people live and walk. The spatial density will be achieved via rapid measurements on a mobile platform. This sensor will quantify spatial disparities in cities of the toxics, HCHO and NO2, as well as carbon monoxide and carbon dioxide for better source identification. These species are detected in the mid infrared by laser absorption spectroscopy, and fiberoptics are used. Tasks accomplished include identification and testing of the appropriate spectroscopic regions; coupling of laser light into a fiberoptic system; development of software to control miniature electronics to scan and control two lasers simultaneously; coupling of the mid infrared fiber into a multipass cell for enhanced pathlength and sensitivity; characterization of sources of instrument noise; and design work for a Phase II prototype.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Scalable and Cost-Effective Solution to the U.S. Housing Crisis: A Case Study on Locally Manufactured Modular Multifamily Housing

This case study assesses waste management efficiencies in modular buildings compared to traditional construction methods. We focus on the modular 1-bedroom Model/Z unit by Model Z Modular, LLC. As part of the collaboration between Model Z Modular and the National Renewable Energy Laboratory, we analyzed waste metrics from design through construction, contrasting these findings against conventional stick-built and site-built multifamily buildings. The Model/Z unit is part of a strategic effort to address affordable housing shortages in South Los Angeles, where household income challenges are pronounced. The unit is produced in a state-of-the-art 150,000 sq. ft. modular manufacturing facility located within the city it is serving, and has so far supported the production of over 1,500 affordable housing units. Model/Z units have been used in projects with as many as 195 units, achieving large economies of scale and time. Our analysis demonstrates that modular construction reduces waste compared to traditional methods. This reduction is achieved through precise prefabrication techniques, the implementation of new framing methods, the concentration of workforce expertise, and streamlined logistics, which optimize material use and greatly reduce on-site handling. Additionally, local manufacturing minimizes transportation needs, improving overall project efficiency. The Model/Z unit exemplifies a scalable solution for enhancing housing affordability by optimizing resource utilization and minimizing associated costs. These methods support the delivery of high-quality units at reduced expenses, addressing critical urban housing shortages effectively. This case study underscores Model Z Modular's commitment to producing affordable, quality housing while fostering economic opportunities through job creation and training programs.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

LandCast Mosaic: Reconstructing Global Population Distributions, 1975-2025

LandCast Mosaic (LCM) provides a global, high-resolution gridded population dataset spanning 1975–2025, representing annual, scenario-consistent estimates of daytime, nighttime, and ambient population distributions. LCM builds on the 2025 LandScan Mosaic (LSM) population data by backcasting to earlier years using historical changes in built-surface area derived from the Global Human Settlement Layer (GHSL) and authoritative population counts from international datasets. The workflow scales 2025 building-informed gridded population estimates according to observed changes in built surface, applies linear interpolation for intermediate years, and normalizes estimates to match administrative- and country-level totals. The resulting dataset offers consistent, globally gridded population estimates over fifty years, suitable for temporal analyses of population dynamics, disaster risk modeling, and urban planning applications.

97 MATHEMATICS AND COMPUTING↗

Satellite Embedding-Based Population Imputation for Areas with Missing Building Footprint Data: A Computer Vision-Based Approach

High-resolution population modeling is important for supporting effective decision-making across diverse sectors. LandScan Mosaic generates population estimates at the level of individual buildings and aggregates them to 3 arc-second grids, and this approach performs well in regions where building footprint data are comprehensive and reliable. However, large portions of the globe still suffer from incomplete, sparse, or entirely missing building stock datasets, creating a structural limitation for strictly building-based population models. To address this research gap, this study proposes a computer vision-based framework that employs Google Earth Engine satellite embeddings and UNet, which allows us to directly impute grid-level population estimates in building-data-deficient areas. Applied to Taiwan as a case study, the framework achieved strong predictive performance with R$^{2}$ of 0.89, RMSE of 18.70, and MAE of 8.41, outperforming traditional machine learning approaches. Notably, the proposed framework effectively addressed building false-positive errors inherent in Global Human Settlement Layer (GHSL) data, correctly identifying uninhabited areas that were erroneously classified as populated. The framework also offers significant advantages for global population mapping, particularly in terms of scalability and temporal consistency, thereby extending the coverage and accuracy of high-resolution population products in data-scarce regions worldwide. Urban planners, decision makers, and related stakeholders can obtain granular population distributions to support more accurate and targeted infrastructure investment, service delivery, resource allocation, and risk assessment decisions.

97 MATHEMATICS AND COMPUTING↗

Green Era Anaerobic Digester

Green Era Educational NFP constructed and commissioned the Green Era Renewable Energy & Urban Farming Campus in Chicago’s Auburn Gresham neighborhood. The project transformed a long-vacant brownfield site into a commercial-scale anaerobic digestion facility that converts food waste into renewable natural gas and nutrient-rich material for agricultural use. The facility can process up to 80,000 wet tons of food waste annually and supports approximately 15 permanent jobs while advancing food waste diversion, renewable energy production, nutrient recovery and community revitalization.

03 NATURAL GAS↗

Potential Energy, Demand, Emissions, and Cost Savings Distributions for Buildings in a Utility’s Service Area

Several companies, universities, and national laboratories are developing urban-scale energy modeling that allows the creation of a digital twin of buildings for the simulation and optimization of real-world, city-sized areas. Prior to simulation-based assessment, a baseline of savings for a set of utility-defined use cases was established to clarify the initial business case for specific energy efficient building technologies. In partnership with a municipal utility, 178,337 OpenStudio and EnergyPlus models of buildings in the utility’s 1400 km 2 service area were created, simulated, and assessed with measures for quantifying energy, demand, cost, and emissions reductions of each building. The method of construction and assumptions behind these models is discussed, definitions of example measures are provided, and distribution of savings across the building stock is provided under a maximum technical adoption scenario.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Quality Control Methods for Advanced Metering Infrastructure Data

While urban-scale building energy modeling is becoming increasingly common, it currently lacks standards, guidelines, or empirical validation against measured data. Empirical validation necessary to enable best practices is becoming increasingly tractable. The growing prevalence of advanced metering infrastructure has led to significant data regarding the energy consumption within individual buildings, but is something utilities and countries are still struggling to analyze and use wisely. In partnership with the Electric Power Board of Chattanooga, Tennessee, a crude OpenStudio/EnergyPlus model of over 178,000 buildings has been created and used to compare simulated energy against actual, 15-min, whole-building electrical consumption of each building. In this study, classifying building type is treated as a use case for quantifying performance associated with smart meter data. This article attempts to provide guidance for working with advanced metering infrastructure for buildings related to: quality control, pathological data classifications, statistical metrics on performance, a methodology for classifying building types, and assess accuracy. Advanced metering infrastructure was used to collect whole-building electricity consumption for 178,333 buildings, define equations for common data issues (missing values, zeros, and spiking), propose a new method for assigning building type, and empirically validate gaps between real buildings and existing prototypes using industry-standard accuracy metrics.

24 POWER TRANSMISSION AND DISTRIBUTION↗

JHU Baltimore iButton data

Temperature and Relative Humidity data from a low cost sensor ("iButton") network deployed in Baltimore in summer 2015, 2016, 2017, 2021, and 2022. Initial deployment described in Scott, A., Zaitchik, B., Waugh, D., O'Meara, K. 2017. Intra-Urban temperature variability in Baltimore. Journal of Applied Meteorology and Climatology, 56(1): 159-171. doi: 10.1175/JAMC-D-16-0232.1

applied meteorology↗

CLMU Anthropogenic Heat Sensitivity Experiments

User namelist settings, code changes, and driving scripts to set to CLM5 on NERSC for deciphering the sensitivity of urban canopy air temperature to anthropogenic heat flux experiments. More details are available in README.md.

Earth Systems↗

CLMU Interactions between UHIs and HWs Experiments

User namelist settings, code changes, and driving scripts to set to CLM5 on NERSC for investigating the interactions between urban heat islands (UHI) and heat waves (HWs) at the continental and daily mean scales over the Contiguous United States (CONUS). More details are available in README.md.

Climate Change↗

PSU-BSEC Doppler Lidar Processed Scans

This data repository includes the processed vertically staring measurements (stare files) made by the Pennsylvania State University (PSU) Doppler Lidar as a part of the Baltimore Social-Environmental Collaborative Urban Integrated Field Laboratory (BSEC UIFL). The PSU Doppler Lidar measures aerosol backscatter intensity (m-1 sr-1), signal-to-noise ratio, and radial velocity (i.e., vertical velocity in the case of stare files, units: m/s) at approximately 1 Hz temporal resolution and 30 m spatial resolution. Future updates will include angled scans, sky cam images, example figures, and the original .hpl files. For further information, please email Nicholas Prince, nec5299@psu.edu.

Air Quality↗