AndreaBozzo/ceres-open-data-index huggingface dataset:
See appendices K-N in report at http://ofmpub.epa.gov/eims/eimscomm.getfile?p_download_id=530693

See report at: http://ofmpub.epa.gov/eims/eimscomm.getfile?p_download_id=530693. 

This dataset is associated with the following publication:
Julius , S., J. Blue, and N. Hiremath. Urban Resilience to Climate Change: Washington, DC and Worcester, MA Case Studies. U.S. Environmental Protection Agency, Washington, DC, USA, 2017.

Tags: adaptation, climate-change, indicators, mixed-methods, qualitative-indicators, quantitative-indicators, urban-resilience, vulnerability, washington-dc, worcester-ma
Organization: U.S. Environmental Protection Agency
Aaron Journal article datasets

All figures used in the journal article are in netCDF format. 

This dataset is associated with the following publication:
Sims, A., K. Alapaty , and S. Raman. Sensitivities of Summertime Mesoscale Circulations in the Coastal Carolinas to Modifications of the Kain–Fritsch Cumulus Parameterization.   Monthly Weather Review. American Meteorological Society, Boston, MA, USA, 145(11): 4381-4399, (2017).

Tags: deep-convection, precipitation-cloud-life-cloud-cover, weather-prediction
Organization: U.S. Environmental Protection Agency
Photocatalytic C-H Activation and Oxidative Esterification Using Pd@g-C3N4

Graphitic carbon nitride supported palladium nanoparticles, Pd@g-C3N4, have been synthesized and utilized for the direct oxidative esterification of alcohols using atmospheric oxygen as a co-oxidant via photocatalytic C-H activation. 

This dataset is associated with the following publication:
Verma, S., R.B.N. Baig, R. Varma, and M. Nadagouda. Photocatalytic CH activation and oxidative esterification using Pd@g-C3N4.   ACS Sustainable Chemistry & Engineering. American Chemical Society, Washington, DC, USA, 309: 248-252, (2018).

Tags: alcohols, c-h-activation, heterogeneous-catalysis, oxidative-esterification, visible-light
Organization: U.S. Environmental Protection Agency
Predicting_Systemic_Toxicity_Effects_ArchTox_2017_Data

In an effort to address a major challenge in chemical safety assessment, alternative approaches for characterizing systemic effect levels, a predictive model was developed. Systemic effect levels were curated from ToxRefDB, HESS-DB and COSMOS-DB from numerous study types totaling 4382 in vivo studies for 1201 chemicals. Observed systemic effects in mammalian models are a complex function of chemical dynamics, kinetics, and inter- and intra-individual variability. In order to address the complexity problem, systemic effect levels were modeled at the study-level by leveraging study covariates (e.g., study type, strain, administration route) in addition to multiple descriptor sets, including chemical (ToxPrint, PaDEL, and Physchem), biological (ToxCast), and kinetic descriptors. Using Random Forest modeling with cross-validation and external validation procedures, study-level covariates alone accounted for approximately 20% of the variance reducing the root mean squared error (RMSE) from 0.96 log10 mg/kg/day to 0.85 log10 mg/kg/day, providing a baseline performance metric (lower expectation of model performance). A consensus model developed using a combination of study-level covariates, chemical, biological, and kinetic descriptors explained a total of 38% of the variance with an RMSE of 0.76 log10 mg/kg/day. A benchmark model (upper expectation of model performance) was also developed with an RMSE of 0.5 log10 mg/kg/day by incorporating study-level covariates and the mean effect level per chemical. To achieve a representative chemical-level prediction, the minimum study-level predicted and observed effect level per chemical were compared reducing the RMSE from 1.1 to 0.8 log10 mg/kg/day. Although biological descriptors did not improve model performance, the final model was enriched for biological descriptors that indicated xenobiotic metabolism gene expression, oxidative stress, and cytotoxicity, demonstrating the importance of accounting for kinetics and non-specific bioactivity in predicting systemic effect levels. Herein, we have generated an externally predictive model of systemic effect levels for use as a safety assessment tool and have generated forward predictions for thousands of chemicals. 

This dataset is associated with the following publication:
Truong, L., G. Ouedraogo, L. Pham, J. Clouzeau, S. Loisel-Joubert, D. Blanchet, H. Noçairi, W. Setzer, R. Judson, C. Grulke, K. Mansouri, and M. Martin. (Archives of Toxicology) Predicting In Vivo Effect Levels for Repeat Dose Systemic Toxicity using Chemical, Biological, Kinetic and Study Covariates.   Archives of Toxicology. Springer, New York, NY, USA, 92(2): 587-600, (2018).

Tags: actor, effect-levels, predictive-toxicity, systemic-effects, toxcast, toxrefdb
Organization: U.S. Environmental Protection Agency
EPIC Forest LAI Dataset: LAI estimates generated from the USDA Environmental Policy Impact Climate (EPIC) model (a widely used, field-scale, biogeochemical model) on four forest complexes spanning three physiographic provinces in VA and NC.

This data depicts calculated and validated LAI estimates generated from the USDA Environmental Policy Impact Climate (EPIC) model (a widely used, field-scale, biogeochemical model) on four forest complexes spanning three physiographic
provinces in Virginia and North Carolina. Measurements of forest composition (species and number), LAI, tree diameter, basal area, and canopy height were recorded at each site during the 2002 field season. Calibrated EPIC results show stand-level temporally resolved LAI estimates with R2 values ranging from 0.69 to 0.96, and stand maximum height estimates within 20% of observation. 

This dataset is associated with the following publication:
Iiames, J., E. Cooter, D. Schwede, and J. Williams. A Comparison of Simulated and Field-Derived Leaf Area Index (LAI) and Canopy Height Values from Four Forest Complexes in the Southeastern USA.   Forests. MDPI AG, Basel,  SWITZERLAND, 9(1): 26, (2018).

Tags: atmospheric-flux, epic, lai, mixed-forest, nitrogen-deposition, southeastern-usa, unmanaged
Organization: U.S. Environmental Protection Agency
Minimal_Set_of_In_Vitro_ER_Agonist_Assays_Selection_RegToxPharm_Data

A dataset for the manuscript which demonstrates that it is possible to achieve levels of performance equivalent to the full 16 assay ER agonist model against both in vitro and in vivo reference chemical sets, using only 4 assays in the simplest “subset” ER agonist model. 

This dataset is associated with the following publication:
Judson, R., K. Houck, E. Watt, and R. Thomas. (REGULATORY TOXICOLOGY AND PHARMACOLOGY) On Selecting a Minimal Set of In Vitro Assays to Reliably Determine Estrogen Agonist Activity.   REGULATORY TOXICOLOGY AND PHARMACOLOGY. Elsevier Science Ltd, New York, NY, USA, 91: 39-49, (2017).

Tags: actor, edsp-models, toxcast
Organization: U.S. Environmental Protection Agency
Kaushal et al. 2017 (Applied Geochemistry) Human-accelerated weathering increases salinization, major ions, and alkalinization in fresh water across land use

•Base cations increased in drinking water over ∼50 years coinciding with urbanization.
•DIC, cations, Si, SO42- and pH in streams increased with impervious surface cover.
•Road salts and weathering of impervious surfaces were major sources of ions.
•Base cations and pH contributed to alkalinization from headwaters to coastal waters.
•Increased ions impact drinking water, infrastructure, and coastal alkalinization. 

This dataset is associated with the following publication:
Kaushal, S., S. Duan, T. Doody, S. Haq, R. Smith, T. Newcomer Johnson, K. Delany Newcomb, J. Gorman, N. Bowman, P. Mayer, K.L. Wood, K.T. Belt, and W.P. Sack. Human-accelerated weathering increases salinization, major ions, and alkalinization in fresh water across land use.   APPLIED GEOCHEMISTRY. Elsevier Science Ltd, New York, NY, USA, 83: 121-135, (2017).

Tags: alkalinization, base-cations, drinking-water, impervious-surface-cover, infrastructure, land-use, road-salt, salinization, weathering
Organization: U.S. Environmental Protection Agency
U.S. Geological Survey: Surface-Water Historical Instantaneous Data for the Nation: Build Time Series

The USGS historical data base contains historical surface water discharge volume data for all 16,658 surface water sites that have current conditions. 

This dataset is associated with the following publication:
Landis , M., A. Kamal, K. Kovalcik , C. Croghan , G. Norris , and A. Bergdale. The Impact of Commercially Treated Oil and Gas Produced Water Discharges on Bromide Concentrations and Modeled Brominated Trihalomethane Disinfection Byproducts at two Downstream Municipal Drinking Water Plants in the Upper Allegheny River, Pennsylvania, USA.   SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM,  NETHERLANDS, 542(2016): 505-520, (2016).

Tags: source-attribution, specific-conductivity
Organization: U.S. Environmental Protection Agency
Total Deposition of Nitrogen and Sulfur from Measurement-Model Fusion for 2010

Deposition values for the continguous United States are developed from a measurement-model fusion approach that used data from the Community Multiscale Air Quality Model and the Clean Air Status and Trends Network. 

This dataset is associated with the following publication:
Schwede, D., A. Cole, R. Vet, and G. Lear. Ongoing U.S.-Canada Collaboration on Nitrogen and Sulfur Deposition.   EM Magazine. Air and Waste Management Association, Pittsburgh, PA, USA,  June, (2019).

Tags: acid-rain, atmospheric-deposition, total-deposition, us-canada-air-quality-agreement
Organization: U.S. Environmental Protection Agency
IATA-Bayesian Network Model for Skin Sensitization Data

Since the publication of the Adverse Outcome Pathway (AOP) for skin sensitization, there have been many efforts to develop systematic approaches to integrate the information generated from different key events for decision making. The types of information characterizing key events in an AOP can be generated from in silico, in chemico, in vitro or in vivo approaches. Integration of this information and interpretation for decision making are known as integrated approaches to testing and assessment or IATA. One such IATA that has been developed was published by Jaworska et al (2013) which describes a Bayesian network model known as ITS-2. The current work evaluated the performance of ITS-2 using a stratified cross validation approach.  We also characterized the impact of refinements to the network by replacing the most significant component, the output from a commercial expert system TIMES-SS with structural alert information readily generated from the freely available OECD QSAR Toolbox. Lack of any structural alert flags or TIMES-SS predictions, yielded a sensitization potential prediction of 79% +3%/-4%. If the TIMES-SS prediction was replaced by an indicator for the presence of a structural alert, the network predictivity increased to 84% +2%/-4%, which was only slightly less than found for the original network (89% &plusmn;2%). The local applicability domain of the original ITS-2 network was also evaluated using reaction mechanistic domains to better understand what types of chemicals ITS-2 was able to make the best predictions for &ndash; i.e. a local validity domain analysis.  We ultimately found that the original network was successful at predicting which chemicals would be sensitizers, but not at predicting their relative potency. 

This dataset is associated with the following publication:
Fitzpatrick, J., and G. Patlewicz. (SAR AND QSAR IN ENVIRONMENTAL RESEARCH) Application of IATA - A case study in evaluating the global and local performance of a Bayesian Network model for Skin Sensitization.   SAR AND QSAR IN ENVIRONMENTAL RESEARCH. Taylor & Francis, Inc., Philadelphia, PA, USA, 28(4): 297-310, (2017).

Tags: bayesian-network-model, dsstox, iata, its, qsar, skin-sensitization
Organization: U.S. Environmental Protection Agency
Judson_Mansouri_Automated_Chemical_Curation_QSAREnvRes_Data

Here we describe the development of an automated  KNIME workflow to curate and correct errors in the structure and identity of chemicals using the publically available PHYSPROP physico-chemical properties and environmental fate datasets. The workflow first assembles structure-identity pairs using up to four provided chemical identifiers, including chemical name, CASRNs, SMILES, and MolBlock. Problems detected  included errors and mismatches in chemical structure formats, identifiers, and various structure validation issues, including hypervalency and stereochemistry descriptions. Subsequently, a machine learning procedure was applied to evaluate the impact of this curation process. The performance of QSAR models built on only the highest quality subset of the original dataset was compared to the larger curated and corrected data set. The latter showed statistically improved predictive performance. The final workflow was used to curate the full list of PHYSPROP datasets, and is being made publically available for further usage and integration by the scientific community. 

This dataset is associated with the following publication:
Mansouri, K., C. Grulke, A. Richard, R. Judson, and A. Williams. (SAR AND QSAR IN ENVIRONMENTAL RESEARCH) An automated curation procedure for addressing chemical errors and inconsistencies in public datasets used in QSAR modeling.   SAR AND QSAR IN ENVIRONMENTAL RESEARCH. Taylor & Francis, Inc., Philadelphia, PA, USA, 27(11): 911-937, (2016).

Tags: actor, data-curation, dsstox, open-data, physicochemical-properties, qsar-modeling
Organization: U.S. Environmental Protection Agency
Impact of noise and ozone on cardiovascular function in rats

This dataset includes raw data used to generate figures for the manuscript describing the effects of noise and ozone on cardiovascular function in rats. 

This dataset is associated with the following publication:
Hazari, M., K. Phillips, K. Stratford, A.M. Khan, L. Thompson, W. Oshiro, G. Hudson, D. Herr, and A. Farraj. Exposure to intermittent noise exacerbates the cardiovascular response of Wistar-Kyoto Rats to Ozone Inhalation and Arrhythmogenic Challenge.   Cardiovascular Toxicology. Humana Press Incorporated, Totowa, NJ, USA, 21(4): 336-348, (2021).

Tags: air-pollution, cardiovascular, noise, ozone, radiotelemetry
Organization: U.S. Environmental Protection Agency
HTTK R Package v1.5 - Identifying populations sensitive to environmental chemicals by simulating toxicokinetic variability

httk: High-Throughput Toxicokinetics

Functions and data tables for simulation and statistical analysis of chemical toxicokinetics ("TK") using data obtained from relatively high throughput, in vitro studies. Both physiologically-based ("PBTK") and empirical (e.g., one compartment) "TK" models can be parameterized for several hundred chemicals and multiple species. These models are solved efficiently, often using compiled (C-based) code. A Monte Carlo sampler is included for simulating biological variability and measurement limitations. Functions are also provided for exporting "PBTK" models to "SBML" and "JARNAC" for use with other simulation software. These functions and data provide a set of tools for in vitro-in vivo extrapolation ("IVIVE") of high throughput screening data (e.g., ToxCast) to real-world exposures via reverse dosimetry (also known as "RTK"). 

This dataset is associated with the following publication:
Ring, C., R. Pearce, W. Setzer, B. Wetmore, and J. Wambaugh. (Environment International)  Refining high-throughput prioritization of environmental chemicals to include inter-individual variability across subpopulations.   ENVIRONMENT INTERNATIONAL. Elsevier Science Ltd, New York, NY, USA, 106: 105-118, (2017).

Tags: expocast, exposure, high-throughput-toxicokinetics, httk, in-vitro-in-vivo-extrapolation, pbpk-reverse-dosimetry, pbtk, physiologically-based-pharmacokinetic-model, r-package, toxcast
Organization: U.S. Environmental Protection Agency
Computational Model of Secondary Palate Fusion and Disruption ChemResTox Data

Morphogenetic events are driven by cell-generated physical forces and complex cellular dynamics. To improve our capacity to predict developmental effects from cellular alterations, we built a multi-cellular agent-based model in CompuCell3D that recapitulates the cellular networks and collective cell behavior underlying growth and fusion of the mammalian secondary palate. The model incorporated multiple signaling pathways (TGF?, BMP, FGF, EGF, SHH) in a biological framework to recapitulate morphogenetic events from palatal outgrowth through midline fusion. It effectively simulated higher-level phenotypes (e.g., midline contact, medial edge seam (MES) breakdown, mesenchymal confluence, fusion defects) in response to genetic or environmental perturbations. Perturbation analysis of various control features revealed model functionality with respect to cell signaling systems and feedback loops for growth and fusion, diverse individual cell behaviors and collective cellular behavior leading to physical contact and midline fusion, and quantitative analysis of the TGF/EGF switch that controls MES breakdown – a key event in morphogenetic fusion. The virtual palate model was then executed with theoretical chemical perturbation scenarios to simulate switch behavior leading to a disruption of fusion following chronic (e.g., dioxin) and acute (e.g., retinoic acid, hydrocortisone) toxicant exposures. This computer model adds to similar systems models toward a ‘virtual embryo’ for simulation and quantitative prediction of adverse developmental outcomes following genetic perturbation and/or environmental. 

This dataset is associated with the following publication:
Hutson, S., M. Leung, N. Baker, R. Spencer, and T. Knudsen. (CHEMICAL RESEARCH IN TOXICOLOGY) Computational Model of Secondary Palate Fusion and Disruption.   CHEMICAL RESEARCH IN TOXICOLOGY. American Chemical Society, Washington, DC, USA, 30(4): 965-979, (2017).

Tags: agent-based-model, childrens-health, compucell3d, computational-biology, developmental-toxicity, morphogenetic-fusion, predictive-toxicology, tipping-points, vembryo, virtual-embryo, virtual-tissues
Organization: U.S. Environmental Protection Agency
Functional Profile of Sediment Layers

A table (DP_KEGG.xlsx) contains rows as KEGG Orthology (KO), columns as sediment layers, and entries representing the abundance of each KO. 

This dataset is associated with the following publication:
Gomez-Alvarez, V., H. Liu, J. Pressman, and D. Wahman. Metagenomic Profile of Microbial Communities in a Drinking Water Storage Tank Sediment after Sequential Exposure to Monochloramine, Free Chlorine, and Monochloramine.   ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 1(5): 1283-1294, (2021).

Tags: denitrification, drinking-water, functional-profile, kegg, ko, metabolic-pathways, metagenomes, microbiome, nitrification, storage-tank-sediment, waterborne-pathogens
Organization: U.S. Environmental Protection Agency
Retrospective_Mining_of_Tox_Data_Anemia_Case_Study_RegToxPharm Data

Data from a study to critically examine some of the issues of using data from ToxRefDB, a database largely composed of guideline studies for pesticidal active ingredients, using a case study focusing on chemically-induced anemia. 

This dataset is associated with the following publication:
Judson, R.S., M. Martin, G. Patlewicz, and C.E. Wood. (Reg. Tox. Pharm.) Retrospective Mining of Toxicology Data to Discover Multispecies and Chemical Class Effects: Anemia as a Case Study.   REGULATORY TOXICOLOGY AND PHARMACOLOGY. Elsevier Science Ltd, New York, NY, USA, 86: 74-92, (2017).

Tags: actor, toxrefdb
Organization: U.S. Environmental Protection Agency
Identifying Known Unknowns Using the USEPA CompTox Chemistry Dashboard AnalytBioanlytChem Data

In this research, the performance of the Dashboard for identifying “known unknowns” was evaluated against that of the online ChemSpider database, one of the primary resources used by mass spectrometrists, using multiple previously studied datasets reported in the peer-reviewed literature totaling 162 chemicals. These chemicals were examined using both applications via molecular formula and monoisotopic mass searches followed by rank-ordering of candidate compounds by associated references or data sources.  A greater percentage of chemicals ranked in the top position when using the Dashboard, indicating an advantage of this application over ChemSpider for identifying known unknowns using data source ranking. Additional approaches are being developed for inclusion into a non-targeted analysis workflow as part of the CompTox Chemistry Dashboard. 

This dataset is associated with the following publication:
McEachran, A., J. Sobus, and A. Williams. (Analytical and Bioanalytical Chemistry) Identifying known unknowns using the US EPAs CompTox Chemistry Dashboard.   Analytical and Bioanalytical Chemistry. Springer, New York, NY, USA,  1-7, (2016).

Tags: chemistry-dashboard, dashboards, dsstox, high-resolution-mass-spectrometry, non-targeted-analysis, suspect-screening
Organization: U.S. Environmental Protection Agency
Aerobic oxidation of alcohols in visible light on Pd-grafted Ti cluster

The titanium cluster with the reduced band gap has been synthesized having the palladium nanoparticles over the surface, which not only binds to the atmospheric oxygen but also catalyzes the oxidation of alcohols under visible light. 

This dataset is associated with the following publication:
Verma, S., R.B.N. Baig, M. Nadagouda, and R. Varma. Aerobic oxidation of alcohols in visible light on Pd-grafted Ti cluster.   TETRAHEDRON. Elsevier Science Ltd, New York, NY, USA, 73(38): 5577-5580, (2017).

Tags: aerial-oxidation, heterogeneous-catalysis, palladium-nanoparticle, photoactive, titanium-cluster, visible-light
Organization: U.S. Environmental Protection Agency
CFD Model Data

Data associated with the development of the CFD model for spore deposition in respiratory systems of rabbits and humans. 

This dataset is associated with the following publication:
Kabilan, S., K. Recknagle, R. Jacob, D. Einstein, A. Kuprat, J. Carson, S. Colby, J. Saunders, S. Hines, J. Teeguarden, S. Taft , and R. Corley. Computational Fluid Dynamics Modeling of Bacillus anthracis Spore Deposition in Rabbit and Human Respiratory Airways  [HS4.44.02].   JOURNAL OF AEROSOL SCIENCE. Elsevier Science Ltd, New York, NY, USA,  14, (2016).

Tags: bacillus-anthracis, human, lagrangian-particle-deposition-models, rabbit, spore-deposition, three-dimensional-computational-fluid-dynamics-model
Organization: U.S. Environmental Protection Agency
A sustainable approach to empower the bio-based future: upgrading of biomass via process intensification

An economically viable and environmentally benign continuous flow intensified process has been developed that demonstrates its ability to upgrade biomass into potential biofuels, solvents, and pharmaceutical feedstocks using a bimetallic AgPd@g-C3N4 catalyst. 

This dataset is associated with the following publication:
Varma, R., M. Gonzalez, S. Verma, and K. Tadele. A sustainable approach to empower the bio-based future: upgrading of biomass via process intensification.   GREEN CHEMISTRY. Royal Society of Chemistry, Cambridge,  UK, 19(7): 1624-1627, (2017).

Tags: bio-based-future, biomass, graphitic-carbon-nitride, process-intensification, sustainable
Organization: U.S. Environmental Protection Agency
Hydroxylation of Benzene via C-H Activation Using Bimetallic CuAg@g-C3N4

Bimetallic CuAg@g-C3N4 catalyst system has been designed and synthesized by impregnating copper and silver nanoparticles over the graphitic carbon nitride surface. Its application has been demonstrated in the hydroxylation of benzene under visible light. 

This dataset is associated with the following publication:
Verma, S., R.B.N. Baig, M. Nadagouda, and R. Varma. Hydroxylation of Benzene via C-H Activation Using Bimetallic CuAg@g-C3N4.   ACS Sustainable Chemistry & Engineering. American Chemical Society, Washington, DC, USA, 5(5): 3637-3640, (2017).

Tags: bimetallic-heterogeneous-catalyst, c-h-activation, graphitic-carbon-nitride, hydroxylation-of-benzene, visible-light
Organization: U.S. Environmental Protection Agency