1. Capturing Brownfield Success: A National Glimpse

2. The Brownfields Center (TBC) Carnegie Mellon and the University of Pittsburgh Deborah Lange, PE, DEE (dlange@cmu.edu) Catherine Rakestraw (crakestr@andrew.cmu.edu) Prepared by: The Brownfields Center (TBC) Carnegie Mellon and the University of Pittsburgh Deborah Lange, PE, DEE (dlange@cmu.edu) Catherine Rakestraw (crakestr@andrew.cmu.edu) Prepared for: ISRC ‘99 Pittsburgh, PA September 1999

3. Purpose of Survey  Premise: all brownfield development is successful Capture the multiple definitions of success of a brownfield Observe unique and common trends Explore –variables that impact success –outcomes that demonstrate success

4. Survey Composition 18 statements about “defining brownfield success” –Topics based on previous studies performed by The Brownfields Center –5 options to choose: 5: Strongly Agree 4: Agree 3: Have no opinion 2: Disagree 1: Strongly Disagree

5. Survey Composition 3 open-ended, blanks (“other”) for respondent to add any additional comments General questions: –Geographic information (zip code) –Stakeholder role

6. Survey Population Non-Pilots # of responses = 5737% Pilots  # of responses = 9863% Total # of surveys = 155  Pilot: recipient of a USEPA Brownfield Assessment Pilot Grant

7. Survey Population 10 EPA Regions 43 states –(less AR, ND, UT, HI, AK, ID, OR) 12 stakeholder roles –property owner, regulator, consultant, lender, city/county planner, economic development agency, politician, developer, real estate agent, academic/student, lawyer, other

8. USEPA Regions Represented 9 10 9 2 6 8 3 7 5 4 1 2 Region 1 - 27 Region 2 - 11 Region 3 - 23 Region 4 - 13 Region 5 - 24 Region 6 - 11 Region 7 - 10 Region 8 - 10 Region 9 - 10 Region 10 - 3 EPA Region # of responses

9. Comparison of Responses from Populations Surveyed

10. Initial Observations Majority strongly agrees on community support issues –brownfield development must be consistent with the master plan for the community (Q) –community must be supportive of the proposed development (R) Majority strongly disagrees on incorporation of residential development –not necessary to maximize residential space (K) –the influx of new residents to to the community is not the greatest benefit (O) Non-Pilot respondents place a stronger emphasis on cost minimization (C, D, E)

11. Statement A: It is important to minimize the time required to get the site back into productive reuse.

12. Statement B: It is important to minimize the total cost (including monies from all sources) to develop a site.

13. Statement C: It is important that the costs associated with utility and other infrastructure (except transportation) improvements are minimized.

14. Statement D: It is important that costs associated with traffic and transportation improvements are minimized.

15. Statement E: It is important that the cost of environmental remediation is minimal.

16. Statement F: It is important to maximize the sale/lease price of the property.

17. Statement G: It is important to maximize the developed acreage that can support on-site jobs. # of responses

18. Statement H: It is important to maximize the number of long term jobs created.

19. Statement I: It is important to maximize the acres of developed (or preserved) greenspace.

20. Statement J: It is important to maximize the new real estate and income tax bases.

21. Statement K: It is important to maximize the new residential space. # of responses

22. Statement L: It is important to maximize new office space. # of responses

23. Statement M: It is important to maximize industrial / commercial space. # of responses

24. Statement N: It is important to consider environmental improvements as the greatest benefit of development. # of responses

25. Statement O: It is important to consider the influx of new residents to the community as the greatest benefit of development.

26. Statement P: It is important to consider the improvements to surrounding businesses as the greatest benefit of development.

27. Statement Q: It is important that the development of a brownfield be consistent with the master plan for the community.

28. Statement R: It is important that the community be supportive of the proposed development.

29. Outcomes that Reflect Success % that Agrees & Strongly Agrees

30. Variables that Impact Success % that Agrees & Strongly Agrees

31. Additional Factors (suggested by responses to S, T and U) –Economics –Environmental –Financial –Land Use Planning –Legal / Regulatory –Socio-economics –Stakeholder involvement –Sustainability Multi-dimension issue A variety of issues

32. Economics Who pays/ who benefits? Balance cost and benefits Marketing studies

33. Environmental Human health and the environment Risk Consistency with end use Institutional control Cost effective Secondary impact

34. Financial Public/private partnerships Private investment State/Federal incentives

35. Land Use Planning Master planning Compatibility End goal - end users Neighborhoods Trade-offs Mixed use Limit industrial corridors Accessibility

36. Legal / Regulatory Time and cost Limit attorneys Regulatory agency cooperation

37. Socio-economics Customers/labor force New job creation Job training Environmental justice Improve image/eliminate blight Catalyst for development/multiplier Balance needs and priorities

38. Stakeholder Involvement Accurate information Community communication networks Community buy-in City administration buy-in Key officials support Champions in leadership roles Public/private/community partnership Maximize resources and expertise

39. Sustainability “Smart growth” Quality of life Preservation of greenspace Brownfield prevention Community needs/benefits

40. KEY ELEMENTS OF SUCCESS Partnerships Stakeholder participation Recognition of community Creative financing Productive reuse Creation of new jobs

41. Additional Analyses Differentiation between USEPA Regions Differentiation between stakeholder groups Principal component analysis Proactive application of results

42. Implications for Future Study Given: ‘Success’ will have common features Given: ‘Success’ will have site specific features  Is it reasonable to think that this complexity can be captured in an ‘equation’?