AndreaBozzo/ceres-open-data-index huggingface dataset:
Series Information for the 2019 Cartographic Boundary File KML, Current State Legislative District-Lower Chamber, 1:500,000

The 2019 cartographic boundary KMLs are simplified representations of selected geographic areas from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). These boundary files are specifically designed for small-scale thematic mapping. When possible, generalization is performed with the intent to maintain the hierarchical relationships among geographies and to maintain the alignment of geographies within a file set for a given year. Geographic areas may not align with the same areas from another year. Some geographies are available as nation-based files while others are available only as state-based files.
                
                SLDL stands for State Legislative District Lower Chamber. State Legislative Districts (SLDs) are the areas from which members are elected to state legislatures. The SLDs embody the upper (senate) and lower (house) chambers of the state legislature. Nebraska has a unicameral legislature and the District of Columbia has a single council, both of which the Census Bureau treats as upper-chamber legislative areas for the purpose of data presentation; there are no data by SLDL for either Nebraska or the District of Columbia. A unique three-character census code, identified by state participants, is assigned to each SLD within a state. In Connecticut, Illinois, Louisiana, Maine, Maryland, Massachusetts, Michigan, Ohio, and Puerto Rico, the Redistricting Data Program (RDP) participant did not define the SLDs to cover all of the state or state equivalent area. In these areas with no SLDs defined, the code "ZZZ" has been assigned, which is treated as a single SLD for purposes of data presentation.
                
                The boundaries of the 2018 state legislative districts were provided by state-level participants through the RDP and reflect the districts used to elect members in or prior to the November 2018 election. The Current State Legislative District-Lower Chamber is availiable at the 1:500,000 scale 

Tags: 2019, cartographic boundary, generalized, kml, lower chamber, lower district, shp, state legislative district, u.s, united sates
Organization: U.S. Census Bureau, Department of Commerce
Series Information for the 2019 Cartographic Boundary File Shapefile, Current State Legislative District-Lower Chamber, 1:500,000

The 2019 cartographic boundary shapefiles are simplified representations of selected geographic areas from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). These boundary files are specifically designed for small-scale thematic mapping. When possible, generalization is performed with the intent to maintain the hierarchical relationships among geographies and to maintain the alignment of geographies within a file set for a given year. Geographic areas may not align with the same areas from another year. Some geographies are available as nation-based files while others are available only as state-based files.
                
                SLDL stands for State Legislative District Lower Chamber. State Legislative Districts (SLDs) are the areas from which members are elected to state legislatures. The SLDs embody the upper (senate) and lower (house) chambers of the state legislature. Nebraska has a unicameral legislature and the District of Columbia has a single council, both of which the Census Bureau treats as upper-chamber legislative areas for the purpose of data presentation; there are no data by SLDL for either Nebraska or the District of Columbia. A unique three-character census code, identified by state participants, is assigned to each SLD within a state. In Connecticut, Illinois, Louisiana, Maine, Maryland, Massachusetts, Michigan, Ohio, and Puerto Rico, the Redistricting Data Program (RDP) participant did not define the SLDs to cover all of the state or state equivalent area. In these areas with no SLDs defined, the code "ZZZ" has been assigned, which is treated as a single SLD for purposes of data presentation.
                
                The boundaries of the 2018 state legislative districts were provided by state-level participants through the RDP and reflect the districts used to elect members in or prior to the November 2018 election. The Current State Legislative District-Lower Chamber is availiable at the 1:500,000 scale 

Tags: 2019, boundaries, cartographic boundary, generalized, lower chamber, lower district, shapefile, shp, state legislative district, u.s, united sates
Organization: U.S. Census Bureau, Department of Commerce
Series Information for the 2019 Cartographic Boundary KML Current Secondary School District, 1:500,000

The 2019 cartographic boundary shapefiles are simplified representations of selected geographic areas from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). These boundary files are specifically designed for small-scale thematic mapping. When possible, generalization is performed with the intent to maintain the hierarchical relationships among geographies and to maintain the alignment of geographies within a file set for a given year. Geographic areas may not align with the same areas from another year. Some geographies are available as nation-based files while others are available only as state-based files.
                
                School Districts are single-purpose administrative units within which local officials provide public educational services for the area's residents. The Census Bureau obtains the boundaries, names, local education agency codes, grade ranges, and school district levels for school districts from state officials for the primary purpose of providing the U.S. Department of Education with estimates of the number of children in poverty within each school district. This information serves as the basis for the Department of Education to determine the annual allocation of Title I funding to states and school districts.
                
                The cartographic boundary files include separate files for elementary, secondary and unified school districts. The generalized school district boundaries in this file are based on those in effect for the 2018-2019 school year, i.e., in operation as of January 1, 2019. Current Secondary School District are avialiable at the1:500,000 scale.

Tags: 2019, boundaries, cartographic boundary, generalized, kml, school district, secondary school district, shp, u.s, united sates
Organization: U.S. Census Bureau, Department of Commerce
Series Information for the 2019 Cartographic Boundary Shapefile Current Secondary School District, 1:500,000

The 2019 cartographic boundary shapefiles are simplified representations of selected geographic areas from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). These boundary files are specifically designed for small-scale thematic mapping. When possible, generalization is performed with the intent to maintain the hierarchical relationships among geographies and to maintain the alignment of geographies within a file set for a given year. Geographic areas may not align with the same areas from another year. Some geographies are available as nation-based files while others are available only as state-based files.
            
            School Districts are single-purpose administrative units within which local officials provide public educational services for the area's residents. The Census Bureau obtains the boundaries, names, local education agency codes, grade ranges, and school district levels for school districts from state officials for the primary purpose of providing the U.S. Department of Education with estimates of the number of children in poverty within each school district. This information serves as the basis for the Department of Education to determine the annual allocation of Title I funding to states and school districts.
            
            The cartographic boundary files include separate files for elementary, secondary and unified school districts. The generalized school district boundaries in this file are based on those in effect for the 2018-2019 school year, i.e., in operation as of January 1, 2019. Current Secondary School District are avialiable at the1:500,000 scale.

Tags: 2019, boundaries, cartographic boundary, generalized, school district, secondary school district, shapefile, shp, u.s, united sates
Organization: U.S. Census Bureau, Department of Commerce
Magnetic Fe@g‑C3N4: A Photoactive Catalyst for the Hydrogenation of Alkenes and Alkynes

A photoactive catalyst, Fe@g-C3N4, has been developed for the hydrogenation of alkenes and alkynes using hydrazine hydrate as a source of hydrogen. The magnetically separable Fe@g-C3N4 eliminates the use of high pressure hydrogenation, and the reaction can be accomplished using visible light without the need for external sources of energy. 

This dataset is associated with the following publication:
Baig, N., S. Verma, R. Varma , and M. Nadagouda. Magnetic Fe@g-C3N4: A Photoactive Catalyst for the Hydrogenation of Alkenes and Alkynes.   ACS Sustainable Chemistry & Engineering. American Chemical Society, Washington, DC, USA, 4(3): 1661-1664, (2016).

Tags: earth-abundant-materials, graphitic-carbon-nitride, heterogeneous-catalysis, hydrogenation, nanoferrite, photocatalysis, sustainable-materials-management
Organization: U.S. Environmental Protection Agency
Detection and Quantification of Silver Nanoparticles at Environmentally Relevant Concentrations Using Asymmetric Flow Field−Flow Fractionation Online with Single Particle Inductively Coupled Plasma Mass Spectrometry

The presence of silver nanoparticles (AgNPs) in aquatic environments could potentially cause adverse impacts on ecosystems and human health.  However, current understanding of the environmental fate and transport of AgNPs is still limited because their properties in complex environmental samples cannot be accurately determined.  In this study, the feasibility of using asymmetric flow field-flow fractionation (AF4) connected online with single particle inductively coupled plasma mass spectrometry (spICPMS) to detect and quantify AgNPs at environmentally relevant concentrations was investigated.  The AF4 channel had a thickness of 350 µm and its accumulation wall was a 10 kDa regenerated cellulose membrane.  A 0.02 % FL-70 surfactant solution was used as an AF4 carrier.  With 1.2 mL/min AF4 cross flow rate, 1.5 mL/min AF4 channel flow rate, and 5 ms spICPMS dwell time, the AF4–spICPMS can detect and quantify 40 – 80 nm AgNPs, as well as Ag-SiO2 nanoparticles (51.0 nm diameter Ag core and 21.6 nm SiO2 shell), with good recovery within 30 min.  This system was not only effective in differentiating and quantifying different types of AgNPs with similar hydrodynamic diameters, such as in mixtures containing Ag-SiO2 core-shell nanoparticles and 40 – 80 nm AgNPs, but also suitable for differentiating between 40 nm AgNPs and elevated dissolved Ag content.  The study results indicate that AF4–spICPMS is capable of detecting and quantifying AgNPs and other engineered metal- nanomaterials in environmental samples.  Nevertheless, further studies are needed before AF4–spICPMS can become a routine analytical technique. 

This dataset is associated with the following publication:
Huynh, K.A., E. Siska, E. Heithmar, S. Tadjiki, and S. Pergantis. Detection and Quantification of Silver Nanoparticles at Environmentally Relevant Concentrations Using Asymmetric Flow Field–Flow Fractionation Online with Single Particle Inductively Coupled Plasma Mass Spectrometry.   Analytical Chemistry. American Chemical Society, Washington, DC, USA, 88(9): 4909–4916, (2016).

Tags: characterization, detection, environmental-matrices, nanoparticles, particle-size-distribution, silver
Organization: U.S. Environmental Protection Agency
Dataset of Atmospheric Environment Publication in 2016, Characterization of organophosphorus flame retardants’ sorption on building materials and consumer products

The data presented in this data file is a product of a journal publication. The dataset contains OPFR sorption concentrations on building materials and consumer products and comparison to the i-SVOC model predictions. 

This dataset is associated with the following publication:
Liu , X., M. Allen, and N. Roache. Characterization of organophosphorus flame retardants' sorption on building materials and consumer products.   ATMOSPHERIC ENVIRONMENT. Elsevier Science Ltd, New York, NY, USA, 140: 333-341, (2016).

Tags: material-air-partition-coefficient, material-phase-diffusion-coefficient, opfrs, organophosphorus-flame-retardants, sink, sorption-concentration, tcep, tcpp, tdcpp
Organization: U.S. Environmental Protection Agency
Changes in Landscape Greenness and Climatic Factors over 25 Years (1989–2013) in the USA

The asci files are the probability of the NDVI trend (slope) and the direction of the NDVI trend (+/-).  These files can be mapped in ArcMap using ArcToolbox (conversion tools and asci to raster).  The asci files are for maps in Figures 1,2 and 4 in the publication.

Figures.xlsx; Contains 8 Figures, each in a sheet titled same as in the publication. Except for Figure 3, all figures contain information about labeling the axis in publication. 

This dataset is associated with the following publication:
Nash, M., J. Wickham, J. Christensen, and T. Wade. Changes in Landscape Greenness and Climatic Factors over 25 Years (1989–2013) in the USA.   Remote Sensing. MDPI AG, Basel,  SWITZERLAND, 9(3): 295, (2017).

Tags: autoregression-model, climatic-factors, direct-factors, long-term-monitoring, ndvi-change, usa
Organization: U.S. Environmental Protection Agency
Evaluation of the immunomodulatory effects of 2,3,3,3-tetrafluoro-2-(heptafluoropropoxy)-propanoate (“GenX”) in C57BL/6 mice

Raw data file outputs of serum and urine measurements of GenX in dosed rodents. 

This dataset is associated with the following publication:
Rushing, B., Q. Hu, J. Franklin, R. McMahen, S. Dagnino, C. Higgins, M. Strynar, and J. DeWitt. Evaluation of the Immunomodulatory Effects of 2,3,3,3-tetrafluoro-2-(heptafluoropropoxy)-propanoate (“GenX”) in C57BL/6 Mice.   ENVIRONMENTAL TOXICOLOGY. John Wiley & Sons, Ltd., Indianapolis, IN, USA, 156(1): 179-189, (2017).

Tags: genx, immunotoxicity, per-and-polyfluorinated, serum, urine
Organization: U.S. Environmental Protection Agency
Data sets used in the analysis presented in the manuscript “Regional and Hemispheric Influences on Temporal Variability in Baseline Carbon Monoxide and Ozone over the Northeast US”

This dataset documents that all of the data analyzed in the manuscript "Regional and Hemispheric Influences on Temporal Variability in Baseline Carbon Monoxide and Ozone over the Northeast US " led by doctoral candidate Ms. Ying Zhou of the College of Environmental Science and Forestry at the State University of New York at Syracuse were contributed by non-EPA research groups and entities. 

This dataset is associated with the following publication:
Zhou, Y., H. Mao, K. Demerjian , C. Hogrefe , and J.L. Liu. Regional and hemispheric influences on temporal variability in baseline carbon monoxide and ozone over the Northeast US.   ATMOSPHERIC ENVIRONMENT. Elsevier Science Ltd, New York, NY, USA, 164: 309-324, (2017).

Tags: baseline-co, baseline-o3, emission, meteorology, northeast-u-s, temporal-variability
Organization: U.S. Environmental Protection Agency
Conolly, R.B., Ankley, G.T., Cheng, WY., Mayo, M.L., Miller, D.H., Perkins, E.J., Villeneuve, D.L., and Watanable, K.H. (2017). Quantitative adverse outcome pathways and their application ot predictive toxicology. Environ. Sci. Technol. 51, 4661–4672

A publised mansucript describing a quantitative adverse outcome pathway (qAOP) and its relevance to risk assessment. This dataset is not publicly accessible because: This work describes computational modeling, not acquisition of laboratory data. It can be accessed through the following means: The mansucript is published in Environmental Science and Technology. Format: This ScienceHub entry is associated with the published manuscript:

Quantitative Adverse Outcome Pathways and Their Application to
Predictive Toxicology
Rory B. Conolly,*,† Gerald T. Ankley,‡ WanYun Cheng,† Michael L. Mayo,§ David H. Miller,∥
Edward J. Perkins,§ Daniel L. Villeneuve,‡ and Karen H. Watanabe⊥
†U.S. Environmental Protection Agency, Office of Research and Development, National Health and Environmental Effects Research
Laboratory, Integrated Systems Toxicology Division, Research Triangle Park, North Carolina 27709, United States
‡U.S. Environmental Protection Agency, Office of Research and Development, National Health and Environmental Effects Research
Laboratory, Mid-Continent Ecology Division, Duluth, Minnesota 55804, United States
§Environmental Laboratory, U.S. Army Engineer Research and Development Center, Vicksburg, Mississippi 39180, United States
∥U.S. Environmental Protection Agency, Office of Research and Development, National Health and Environmental Effects Research
Laboratory, Mid-Continent Ecology Division, Grosse Isle, Michigan 48138, United States
⊥School of Mathematical and Natural Sciences, Arizona State University, West Campus, Glendale, Arizona 85306, United States

DOI: 10.1021/acs.est.6b06230
Environ. Sci. Technol. 2017, 51, 4661−4672. 

This dataset is associated with the following publication:
Conolly, R., G. Ankley, W. Cheng, M. Mayo, D. Miller, E. Perkins, D. Villeneuve, and K. Watanabe. Quantitative Adverse Outcome Pathways and Their Application to Predictive Toxicology.   ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 51(8): 4661-4672, (2017).

Tags: adverse-outcome-pathway, aop, computational-model, hazard, qaop, quantitative-aop, risk
Organization: U.S. Environmental Protection Agency
Ozonolysis of α/β-farnesene mixture: analysis of gas-phase and particulate reaction products

Atmospheric oxidation of sesquiterpenes has been of considerable interest recently because of their likely contribution to ambient organic aerosol, but farnesene oxidation has been reported in only a few studies and with limited data. In the present study, a detailed chemical analysis of the organic fraction of gas and particle phases originating from the ozonolysis of a mixture of α-farnesene and β-farnesene was carried out in a 14.5 m3 smog chamber. More than 80 organic compounds bearing OH functionality were detected for the first time in this system in the gas and particle phases. The major secondary organic aerosol (SOA) components included conjugated α farnesene trienols, hydroxyl carboxylic acid and its corresponding lactones, C3–C7 linear dicarboxylic acids, and hydroxy/carbonyl/carboxylic compounds. Of particular importance was 5,6-dihydroxy-6-methylheptan-2-one (DHMHO), which was detected at high concentration. In the gas phase, the main species identified were trienols and their corresponding epoxides and diepoxides. Proposed reaction schemes are provided for selected compounds. A similar analysis was performed for ambient PM2.5 samples collected during summer 2013 as part of the SOAS to determine farnesene contributions to PM2.5. Gas chromatography–mass spectrometry analysis were consistent with the occurrence of several farnesene SOA compounds, indicating the potential impact of farnesene on the regional aerosol burden. The high abundance of DHMHO in chamber SOA and its presence in ambient PM2.5 is particularly important because to our knowledge it is specific to farnesene and therefore could serve as an indicator for farnesene emitted into ambient aerosol. In the absence of authentic standards, however, it is difficult to accurately quantify the contribution of SOA originating from farnesene to ambient PM2.5. 

This dataset is associated with the following publication:
Jaoui, M., M. Lewandowski, J. Offenberg, K. Docherty, and T. Kleindienst. Ozonolysis of α/β-farnesene mixture: Analysis of gas-phase and particulate reaction products.   ATMOSPHERIC ENVIRONMENT. Elsevier Science Ltd, New York, NY, USA, 169: 175-192, (2017).

Tags: air-quality, air-toxics, conjugated-triene-ol, farnesene, ozone, pm2-5, secondary-organic-aerosol, sesquiterpenes
Organization: U.S. Environmental Protection Agency
PPARα-independent transcriptional targets of perfluoroalkyl acids revealed by transcript profiling

Microarray datasets used in the analysis. 

This dataset is associated with the following publication:
Rosen, M., K. Das, J. Rooney, B. Abbott, C. Lau, and C. Corton. PPARα-independent transcriptional targets of perfluoroalkyl acids revealed by transcript profiling.   TOXICOLOGY. Elsevier Science Ltd, New York, NY, USA, 387: 95-107, (2017).

Tags: constitutive-activated-receptor-car, estrogen-receptor, gene-expression-omnibus-accession-numbers, liver-cancer, microarray, perfluorinated-chemicals, peroxisome-proliferator-activated-receptor-alpha, peroxisome-proliferator-activated-receptor-gamma, pfhxs, pfna, pfoa, pfos, stat5b, steatosis
Organization: U.S. Environmental Protection Agency
Data Dictionary for "Comparison of soil sampling and analytical methods for asbestos at the Sumas Mountain Asbestos Site—Working towards a toolbox for better assessment", Version 1 (8/28/2017); by D.A. Vallero (ORD-NERL) and J. Wroble (Region 10).

Definition of terms used in manuscript's technical descriptions, tables and figure. 

This dataset is associated with the following publication:
Wroble, J., T. Frederick, A. Frame, and D. Vallero. Comparison of soil sampling and analytical methods for asbestos at the Sumas Mountain Asbestos Site—Working towards a toolbox for better assessment.   PLoS ONE. Public Library of Science, San Francisco, CA, USA, 12(7): e0180210, (2017).

Tags: activity-based-sampling-abs, asbestos, astm-d-7521, carb-435, decision-unit, epa-200-2, epa-200-7, fbas-iso-10312, naturally-occurring-asbestos, sediment, transmission-electronic-microscopy-tem
Organization: U.S. Environmental Protection Agency
Table 3 LCF Results and Figure S2 LCF data

Table 3 shows the distribution of lead speciation results for soil samples along with fitting error (R factor)
Data for Figure S2 contains the sample spectra and linear combination fitting (LCF) data used to determine results in Table 3. 

This dataset is associated with the following publication:
Kastury, F., R.R. Karna, K.G. Scheckel, and A.L. Juhasz. Correlation between lead speciation and inhalation bioaccessibility using two different simulated lung fluids.   ENVIRONMENTAL POLLUTION. Elsevier Science Ltd, New York, NY, USA, 263 part B: 114609, (2020).

Tags: inhalation-exposure, lead-contaminated-soil, metal-bioavailability, synchrotron-speciation
Organization: U.S. Environmental Protection Agency
Size-Selective Sampling Performance of Six Low-Volume “Total” Suspended Particulate (TSP) Inlets

Results from the comprehensive wind tunnel evaluation of six low-volume aerosol inlets are presented as a function of wind speed and aerodynamic particle diameter. 

This dataset is associated with the following publication:
Vanderpool, R., J. Krug, S. Kaushik, J. Gilberry, A. Dart, and C. Witherspoon. Size-selective sampling performance of six low-volume “total” suspended particulate (TSP) inlets.   AEROSOL SCIENCE AND TECHNOLOGY. Taylor & Francis, Inc., Philadelphia, PA, USA, 52(1): 98-113, (2018).

Tags: aerosol, inlet, inlets, low-volume, particulate, particulates, samplers, size-selective
Organization: U.S. Environmental Protection Agency