This data publication contains the raw, extracted, and derived (e.g., peak areas) mass spectrometry data for illicit drug and mixture samples. These samples were analyzed by wipe-based collection or solvent-extraction, thermal desorption, and a transportable high-resolution time-of-flight mass spectrometer. Data were collected with both an in-line dielectric barrier discharge ionization source and an acetone-dopoant assisted vacuum ultraviolet (VUV) photoionization source.

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.

Supporting information for the NIST Internal Report entitled: Per- and Polyfluoroalkyl Substances - Non-Targeted Analysis Interlaboratory Study Final Report. The files include four comma-separated value (CSV) text files, three of the CSV text files contain summary tables of all per and polyfluoroalkyl substances (PFAS) detected in the three test samples from the interlaboratory report (sample_a_table.csv, sample_b_table.csv, sample_c_table.csv) including the individual laboratory reported identities and their associated identification confidence levels.

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.

A table of known interferences for per- and polyfluoroalkyl substances using mass spectrometry.

Data here contain and describe an open-source structured query language (SQLite) portable database containing high resolution mass spectrometry data (MS1 and MS2) for per- and polyfluorinated alykl substances (PFAS) and associated metadata regarding their measurement techniques, quality assurance metrics, and the samples from which they were produced. These data are stored in a format adhering to the Database Infrastructure for Mass Spectrometry (DIMSpec) project. That project produces and uses databases like this one, providing a complete toolkit for non-targeted analysis.

This data publication contains the mass spectrometry chemical characterization of microplastic and nanoplastic chemical analysis. The data from this study includes mass spectra of pure, mixed, and weathered microplastics and nanoplastics at high and low fragmentation, extracted ion chronograms, Kendrick mass defect plots, code, and the derived and processed data. The data analysis code (MATLAB 2022a*) used for unsupervised learning of cluster and compositional relationships is also included.

Python scripts and Python+Qt graphical user interface for calculating Feldman-Cousins confidence intervals for low-count Poisson processes in the presence of a known background and for Gaussian processes with a physical lower limit of 0.

During work on the new reference equation of state for carbon dioxide [A.H. Harvey, S.A. Tashkun, R. Hellmann, and E.W. Lemmon, J. Phys. Chem. Ref. Data, in preparation], 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