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Public Meetings on Reassessment of PCB Use Authorizations
EPA issued an Advance Notice of Proposed Rulemaking related to potential reassessment of PCB use authorization under the Toxic Substance Control Act. Public comments are due on July 6; EPA will also be holding public meetings. Learn more here…
EPA Proposes Adding 16 Chemicals to the TRI Chemical List
On April 6, 2010, EPA took another important step toward providing communities with additional information about toxic chemicals being released to the environment.
EPA is Providing Communities with Additional Information about the Release of Hydrogen Sulfide into the Environment
The Agency is announcing that it is considering lifting the 1994 Administrative Stay of the Toxics Release Inventory (TRI) reporting requirements for hydrogen sulfide. EPA is now presenting its rationale for why the Stay should be lifted, based on an updated evaluation that includes new information on human health and environmental effects of hydrogen sulfide. Learn more here...
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ECOS is interested hearing your suggestions on topics for an upcoming TRI Webinar.
ECOS is interested hearing your suggestions on topics for an upcoming Webinar and additional topics for future dates. The first Webinar will be held in late October/early November 2009 and be open to the public and all stakeholders. The main purpose of the Webinars is to present and discuss specific TRI-related topics of interest to stakeholders.
- CR2K's blog
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Topic for TRI Webinar
"The considerations necessary when using TRI data in scientific studies (and suggested approaches for researchers)".
Individuals often discuss individual data limitations, but never as a complete tool kit and seldom with approaches to address the limitations when using TRI data. I have seen where researchers well respected in their fields make common mistakes by making the wrong assumption as to what a specific data element means or how it may have been reported to the EPA. Typically the mistakes become apparent when certain data trends are applied at too fine a scale or an assumed exactness is attributed to the data.