Environmental Review Toolkit
Accelerating Project Delivery

Evaluating the Performance of Environmental Streamlining:
Development of a NEPA baseline for Measuring Continuous Performance

5.0 CONCLUSIONS AND RECOMMENDATIONS

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5. 1 Conclusions

As presented in Section 4. 0, this research has resulted in a number of interesting conclusions related to the NEPA EIS process and its relationship with other factors, including the length of the overall project delivery process. A summary listing of the major results is presented below:

  • Based on the first 30 years of NEPA compliance, the typical length of time for preparing an EIS pursuant to NEPA has been either 3. 0 or 3. 6 years, depending on whether the median or mean values are used, respectively;
  • The length of time for preparing an EIS pursuant to NEPA has varied between former FHWA regions, with the greatest time required in Region 1 (4. 5 or 4. 7 years, based on median or mean values, respectively) and the least time required in Region 10 (1. 0 or 2. 2 years, based on median or mean values, respectively);
  • For those projects in which an EIS pursuant to NEPA was required, the mean time required for the entire project development process has been approximately 13. 1 years;
  • For those projects in which an EIS pursuant to NEPA was required, the NEPA process accounted for approximately 27 to 28% of the total time required for the entire project development process, depending on whether the median or mean values are used, respectively;
  • The length of time for preparing an EIS pursuant to NEPA has varied between each of the three decades that have occurred since NEPA was implemented, ranging from a mean of 2. 2 years in the 1970s to a mean of 5. 0 years in the 1990s;
  • The length of time for preparing an EIS pursuant to NEPA has varied depending on whether or not a Section 404 permit was also required, ranging from a mean of 2. 4 years when no Section 404 permit was required to a mean of 4. 3 years when a Section 404 permit was required;
  • The length of time for preparing an EIS pursuant to NEPA has varied depending on whether or not Section 4(f) approval was also required, ranging from a mean of 2. 8 years when no Section 4(f) approval was required to a mean of 4. 7 years when Section 4(f) approval was required;
  • The length of time for preparing an EIS pursuant to NEPA has varied depending on the number of agency meetings held, ranging from a mean of 2. 4 years when fewer than three agency meetings were held to a mean of 4. 5 years when three or more agency meetings were held;
  • The length of time for preparing an EIS pursuant to NEPA has varied depending on the number of public meetings held, ranging from a mean of 2. 7 years when fewer than three agency meetings were held to a mean of 4. 2 years when three or more agency meetings were held; and
  • The length of time for preparing an EIS pursuant to NEPA has varied depending on whether or not noise has been an issue, ranging from a mean of 3. 2 years when noise was not an issue to a mean of 4. 4 years when noise was an issue.

All of the above findings serve as useful information for establishing a baseline condition against which to evaluate future efforts to implement environmental streamlining initiatives within the NEPA process. The fact that these findings are based on a comprehensive analysis of historical data ensures that the baseline conditions that have been identified reflect the best information available for understanding the NEPA process timelines that have been experienced to date. Although there are some limitations inherent in the data, no other better source of information currently exists.

After a few years, when information regarding current and future projects where new environmental streamlining initiatives are employed becomes available, they can be compared against the findings stated above to assess whether there has been any improvement in terms of the length of the NEPA process under a variety of conditions. Unfortunately, it will likely require a number of additional years before any projects in which new streamlining initiatives have been employed actually complete the entire project development process. Nevertheless, the baseline information presented in this report will be available and will continue to be valid for comparing future NEPA projects, regardless of when they become ready to make such comparison.

It should be cautioned, however, that any future comparative efforts utilize data that are similar in nature to the data used to develop the above findings. For instance, the values presented above for the typical length of time to prepare an EIS pursuant to NEPA do not include the time period following signature of the FEIS document and preceding the Record of Decision. Therefore, future efforts should also define the end of the NEPA process as the date of FEIS signature, although the additional time required to complete the Record of Decision can and should be recorded as a separate data field.

5. 2 Recommendations

Since it is assumed that any efforts to collect, analyze and monitor data for ongoing and future projects would essentially follow the same methodology used in this research effort, the primary recommendations to be made reflect potential improvements that could be made to the existing data sources to further enhance such efforts. These include the following:

  1. Require descriptive information in FMIS records — In order to improve upon the ability to capture and utilize a greater percentage of the total FMIS records, it is necessary to ensure that better recordation of descriptive information in those records is implemented. The descriptive fields are critical to the ability to allocate each record to a given EIS project. Although the information in the FMIS records is collectively provided by many FHWA staff members located throughout the country, the FHWA staff that are actually responsible for compiling and maintaining these records could perhaps implement more specific requirements and measures for adequately completing the information requested. These requirements and measures would not improve the quality and usability of the existing records, but they would certainly improve the ability to use future records.

  2. Reuire identification of EIS number in FMIS records — A valuable type of data that would further improve the ability to capture and utilize a greater percentage of FMIS records, as well as to improve the ability to link those records to specific EIS projects, would be the inclusion of the specific EIS number associated with each appropriation number / project number combination. The inclusion of such data would even eliminate the need to provide descriptive information in the FMIS records, although in combination, both types of data would significantly improve the data collection and analysis process. Similar to the above recommendation, the FHWA staff that are specifically responsible for compiling and maintaining the FMIS database could implement requirements and measures for ensuring that the FHWA field staff provide the data in the format necessary for future analysis. Once again, these requirements and measures would not improve the quality and usability of the existing records, but they would certainly improve the ability to use future records.

Consideration should also be given to expanding the baseline sample in order to further reduce the potential for sampling error. As stated in Section 3. 4, the sampling error associated with a sample size of 100 projects, as used in this study, is approximately 9. 1%. Increasing the sample size to 150 projects would decrease the potential for sampling error to approximately 7. 1% while a sample size of 200 projects would reduce it to approximately 5. 8%. A sample size of 300 projects would be required in order to reduce potential for sampling error to only 5. 0%. Of course, a trade-off must be made between the ability to reduce the potential for sampling error and the time and cost associated with providing incremental statistical improvements. Although the sample used in this study is considered to be statistically valid for the research performed, increasing the sample size to 200 projects would further improve the statistical validity of the results. However, if no additional research on this topic is ever conducted, the results included herein do provide a valid and reasonable baseline against which to evaluate future environmental streamlining efforts.


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