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Estimated reading time: 2 minutes
Environmental regulations are supposed to be based on sound science, yet too often either that science is not presented or is deemed insuffiient by permit applicants and others. The result can be administrative appeals and legal challenges that increase time and costs for the applicant and indecision by regulatory agency staff.
At their core, all environmental regulations ask three questions to assess compliance with the relevant law or statute:
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Will the permitted activity adversely effect the natural environment (forecasting)?
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Does the operating activity degrade the natural environment (cause and effect)?
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Are there synergistic or cumulative impacts from multiple activities (spatio-temporal multivariable interactions)?
Answering these questions requires appropriate baseline data. Regardless of permit type or project/activity stage it is necessary to collect physical, chemical, and biological data consistently at defined locations. These data are identified when the sampling program is designed based on the response variable (or variables) of interest and the potential explanatory variables that influence the values observed and measured. These variables are often called dependent (response) and independent (explanatory).
Determining the relevant response and explanatory variables is necessary to demonstrate compliance with CERCLA, CWA, ESA, NEPA, RCRA and all other environmental laws.
The regulatory science that informs technically sound and legally defensible environmental policy and regulatory decisions has two components: analysis of data using appropriate (and correctly applied) statistical models and interpreting the results using established ecological knowledge of ecosystem dynamics.
This work was originally published on the Applied Ecosystem Services, LLC web site at https://www.appl-ecosys.com/blog/regulatory-uncertainties/
It is offered under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International license. In short, you may copy and redistribute the material in any medium or format as long as you credit Dr. Richard Shepard as the author. You may not use the material for commercial purposes, and you may not distribute modified versions.
