SSDn metal dataset

The dataset is an excel file that contains meta data, aquatic toxicity data, and summary tables.

This dataset is associated with the following publication: Lambert, F., S. Raimondo, and M. Barron. Assessment of a New Approach Method for Grouped Chemical Hazard Estimation: The Toxicity-Normalized Species Sensitivity Distribution (SSDn). ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 56(12): 8278-8289, (2022).

Data and Resources

Field Value
accessLevel public
bureauCode {020:00}
catalog_conformsTo https://project-open-data.cio.gov/v1.1/schema
identifier https://doi.org/10.23719/1522898
license https://pasteur.epa.gov/license/sciencehub-license.html
modified 2021-07-20
programCode {020:000}
publisher U.S. EPA Office of Research and Development (ORD)
publisher_hierarchy U.S. Government > U.S. Environmental Protection Agency > U.S. EPA Office of Research and Development (ORD)
references {https://doi.org/10.1021/acs.est.1c05632}
resource-type Dataset
source_datajson_identifier true
source_hash a7c9227a6f85cf282c7f91d3caeeef2c58637594823362544e3fff911067b11f
source_schema_version 1.1
Groups
  • AmeriGEOSS
  • National Provider
  • North America
Tags
  • AmeriGEO
  • AmeriGEOSS
  • CKAN
  • GEO
  • GEOSS
  • National
  • North America
  • United States
  • aquatic-organism
  • aquatic-toxicity
  • extrapolation
  • new-approach-methodologies
isopen False
license_id other-license-specified
license_title other-license-specified
maintainer Mace Barron
maintainer_email barron.mace@epa.gov
metadata_created 2025-09-23T14:28:41.987517
metadata_modified 2025-09-23T14:28:41.987524
notes The dataset is an excel file that contains meta data, aquatic toxicity data, and summary tables. This dataset is associated with the following publication: Lambert, F., S. Raimondo, and M. Barron. Assessment of a New Approach Method for Grouped Chemical Hazard Estimation: The Toxicity-Normalized Species Sensitivity Distribution (SSDn). ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 56(12): 8278-8289, (2022).
num_resources 1
num_tags 12
title SSDn metal dataset