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When looking at streamlining the NEPA (National Environmental Policy Act) process without reducing quality everything is open to reconsideration. Quantifying subjectivity and reordering tasks can dramatically reduce the time to produce a technically sound and legally defensible EIS and Record of Decision (ROD), but there is more that can be done.
Data collection and numerical modeling offer opportunities to increase EIS quality while decreasing the time involved. The data are used to characterize existing environments and predict alternative future environments.
Existing environments characterized are economic, natural, and societal. These are the baselines against which changes resulting from the various project alternatives will be compared. Because alternatives are inexact forecasts of future environments, as long as the baselines are reasonable they serve the intended purpose. Where quantitative values are appropriate (where measurements are meaningful) there could be variability on time scales from hours to decades or longer. Since it is impossible to capture all this variability we can take few measurements and base our characterization on them. Rarely do we gain more insight or useful information by collecting data for a year or more. When quantitative values are not appropriate (e.g., recreational opportunities, aesthetics, quality of life, environmental justice) we can assign qualitative terms (some, many, high, good) on relative scales.
Forecasting alternative future environments is highly qualitative. Mine life is generally at least 10 years, and can easily be 100 years before the site is mined out, every facility closed, and the entire area reclaimed. A lot will happen in that time that cannot be predicted and accounted for in the descriptions of the affected environments. Therefore, it is technically sound to describe these alternative future environments relative to the existing environment. Future components can be described as smaller, steeper, drier, or fewer than currently exists. Making informed qualitative comparisons is also less likely to be challenged on specific numeric values. Describing the anticipated effects of the project alternatives qualitatively can be done quickly, and include a range of technical expert opinions, compared with trying to develop quantitative predictions based on models or Best Professional Judgment.
While the above may initially appear to be inadequate, they fit the purpose of NEPA, particularly an EIS. The EIS is not used to determine whether the project is approved, but to select the alternative that would avoid, minimize, or adequately mitigate for any undesired negative impacts on the environments. The subsequent operating permit is only one of many regulatory constraints on the operator. Compliance with those permit stipulations and conditions, plus any revisions justified when each is renewed, provide adequate adjustments to the assumptions of the alternatives made before the project became operational.
Since the EIS is used to make an informed decision based on forecasts projected decades into the future, a high degree of quantitative accuracy cannot be justified for the time and expense involved. Adjustments to changing environments over the project life are made with renewed permits and demonstration by the operator of compliance with those conditions.
This work was originally published on the Applied Ecosystem Services, LLC web site at https://www.appl-ecosys.com/blog/streamlining-nepa-compliance/
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.