Updated April 2025. Here we provide hourly observations of carbon dioxide (CO2), methane (CH4), and carbon monoxide (CO) mole fractions in dry air from tower- and rooftop-based sites in the Los Angeles Megacity Carbon Project network. Each *.tgz (tar/gzip) archive contains data files for a given site location, named by its 3-letter code. To extract *.tgz files on a unix platform, use "tar -xvzf <filename>".

Reference functional model for the activities and processes involved in production (e.g., designing, manufacturing, and recovering products/materials) in a circular economy. The model includes inputs and outputs of each activity, as well as factors that constrain and enable the activities (controls and mechanisms), using the IDEF0 methodology. It provides a baseline scenario that is relevant for stakeholders across product development and supply chain, including business strategists, material suppliers, designers, manufacturers, consumers, and recovers/recyclers.

To bridge the gap between the development of greenhouse gas (GHG) and air quality (AQ) emission inventories, we developed the GReenhouse gas And Air Pollutant Emissions System (GRA2PES), which provides self-consistent GHG and AQ emissions over the contiguous U.S. This inventory provides emissions at 4 km x 4 km spatial resolution with year, month, day-of-week, and diurnal temporal information. GRA2PES utilizes datasets from the U.S. Energy Information Administration (EIA) and the U.S.

Sim-PROCESD is a discrete event simulation package written in Python that is designed to model the behavior of discrete manufacturing systems. Specifically, it focuses on asynchronous production lines. It also provides functionality for modeling the degradation and maintenance of machines in these systems. Sim-PROCESD provides class definitions for manufacturing devices/components that can be configured by the user to model various real-world manufacturing systems.

Open-path near-IR dual-comb spectra collected at Mauna Loa Observatory in spring 2021, fit with different absorption models (eg HITRAN) and compared against NOAA GML's record.

This dataset contains data used in the investigation of Universally Unique Identifiers (UUIDs) that will enable a standards-based digital thread of product data in ISO 10303-242. Included are EXPRESS schema used for implementation and .stp files that were exported from native CAD (CATIA V5, Creo, and NX). UUIDs were assigned to CAD features during .stp export for each of the four design iterations.

Hestia Fossil Fuel Carbon Dioxide Emissions Inventory for Urban Regions (Hestia FFCO2) provides data products for Los Angeles Basin, Northeast corridor, Indianapolis, and other U.S. Cities. Hestia FFCO2 datasets quantify greenhouse gases (GHG), such as carbon dioxide, emitted by urban regions, since cities are major contributors of anthropogenic GHG emissions. The Hestia FFCO2 datasets provide high spatial and temporal resolution CO2 concentrations at sub-county resolutions and annual/hourly time scales, specific to the region.

An experiment was set up within a machine tool at the National Institute of Standards and Technology (NIST) to test vision-based thermal drift tracking methods. A wireless microscope within a tool holder in the spindle is used to capture videos of image targets attached to the worktable. For each target, one video is captured during spindle rotation orthogonal to the worktable and another video is captured during axis translation orthogonal to the worktable.

During work on the new reference equation of state for carbon dioxide [E.W. Lemmon, A.H. Harvey, and R. Hellmann, NIST Internal Report, to be published in 2025], we obtained unpublished data from several sources. These represent numerical values for data only presented graphically in a publication, or in some cases data not present in the publication at all. With the permission of the authors, we document and deposit these data here so they will be available for future workers.

This is the data presented in the figures of the paper "The effects of advanced spectral line shapes on atmospheric carbon dioxide retrievals" published in J. Quant. Spectrosc. Radiat. Transfer at https://doi.org/10.1016/j.jqsrt.2022.108324