By John Talberth, Erin Gray, Logan Yonavjak, Todd Gartner
Maine (February 2013) – Investments in “green” infrastructure solutions, such as agricultural and forestry best-management practices, are increasingly recognized as cost-effective ways to achieve environmental quality outcomes over a long time-horizon relative to traditional investments in “gray” infrastructure, such as wastewater treatment or water filtration plants. Despite this, there is no consistent and accessible methodology available to decision makers for investigating the financial trade-offs. This paper suggests such a methodology—green-gray analysis (GGA)—and demonstrates its application by considering a green-gray case study involving the Portland Water District (PWD) in Maine.
This application suggests that investing in five green infrastructure options could represent either a cost savings of up to 71 percent over constructing a new filtration plant or a cost increase of up to 44 percent. Uncertainty over green infrastructure efficacy and costs accounted for this wide range of outcomes in six modeled scenarios. The PWD analysis demonstrates the usefulness of a general methodology, but also identifies significant data gaps that need to be filled to make GGA more widely applicable.
By working out the details of a replicable methodology, it is our hope that infrastructure investors who typically opt for gray can routinely evaluate the financial and economic benefits of green in their formal decision-making process.
Three insights emerge from our PWD case study. First, while there are certainly complexities involved, green infrastructure investments can be presented in a manner commensurate with conventional gray investments; the two can indeed be compared dollar-for-dollar, apples-to-apples, by public investment analysts. This suggests that, once fully developed, a GGA methodology could be a standard part of infrastructure investment decisions for a wide variety of settings. Second, the key to an actionable GGA is a robust underlying model that establishes the quantitative relationship between each green infrastructure component and the outcome sought, whether it be regulating pollutants at a specified threshold or generating net public benefits. These models will become more refined and accurate as GGA applications proliferate.
Third, green infrastructure presents additional sources of risk and uncertainty relative to gray. Thus, any GGA must place a heavy emphasis on identifying and mitigating risk and uncertainty through portfolio design (e.g., a green multi-barrier approach), analytical adjustments (e.g., modeling the risk of failure), or sensitivity analysis. Nevertheless, and as demonstrated by the PWD case study, green infrastructure may represent savings large enough to warrant selection, even under conditions of significant uncertainty. A standardized GGA methodology that incorporates accurate cost-estimates and site-specific biophysical models will help investment analysts make the case for green infrastructure, even to the most skeptical budget hawks.
Green versus Gray: Nature’s Solutions to Infrastructure Demands. Solutions. Vol 1, No. 4.