For almost a century, New York City has drawn its drinking water from the Catskill Mountains, more than 100 miles (161km) to the north. In April of 2007, the Environmental Protection Agency (EPA) announced the results of a several-year review of the city’s ongoing programme to maintain clean drinking water supplies with forest and open space conservation in the Catskills rather than the construction of filtration plants. The results were encouraging.
The EPA concluded that as long as the city agreed to set aside $300m over the next 10 years to acquire land and restrain upstate development that causes runoff and pollution, the agency would exempt New York from having to build an $8bn filtration plant. The Catskills aqueduct has been held up as the quintessential example of green infrastructure trumping gray and has prompted cities worldwide to consider alternative solutions to the infrastructure demands of the 21st century.
Cities around the country are starting to realise the economic – to say nothing of environmental – benefits of this shifting reality. A recent analysis by New York City found that green roofs and bioswales could help meet water-quality goals with savings of more than $1bn compared to conventional infrastructure; the Chesapeake Bay could reduce nitrogen loading at less than half the price by using cover crops instead of upgraded wastewater plants.
The City of Philadelphia found that the net present value of green infrastructure for storm-water control ranged from $1.94 to $4.45bn, while gray infrastructure benefits ranged from only $0.06 to $0.14bn over a 40-year period. And using a system of wetlands, North Carolina could minimise storm-water runoff for 47 cents per thousand gallons treated. Using conventional storm-water controls, this figure jumps to $3.24 per thousand gallons.
An emerging hypothesis in environmental management settings is that investment in ecosystem-based green infrastructure solutions provides economically superior environmental quality outcomes when compared to investments in technology-based or “gray” infrastructure. As noted by economists Lucy Emerton and Elroy Bos: “It is increasingly apparent that investment in ecosystems now can safeguard profits in the future, and save considerable costs.”
While there is no single definition, current literature suggests that green infrastructure comprises “all natural, semi-natural and artificial networks of multifunctional ecological systems within, around and between urban areas, at all spatial scales”. Examples of green infrastructure investments include reforestation, installation of grass and riparian buffers, green roofs, porous pavement, urban trees, constructed wetlands, stream restoration and best-management practices for agriculture and forestry.
Many of these assets even appreciate in value over time. For instance, as urban trees mature, they do better at cooling down the urban heat-island effect. As riparian buffers mature, they do better at regulating water quality and flow, and supporting fisheries. This stands in stark contrast to gray infrastructure, which only depreciates.
Comparing green with gray
Although existing case studies are intriguing, green-gray analysis (GGA) is in its infancy and has yet to permeate public infrastructure investment decisions. While calculating the costs and benefits of gray infrastructure is relatively straightforward, placing analysis of green infrastructure costs and benefits on equal footing has not yet been formalised. As a result, financial savings potentially gained from green infrastructure investments are not considered or realised. Additionally, ancillary ecosystem service benefits are largely excluded from investment and infrastructure decisions. This methodological gap presents a formidable barrier to public infrastructure investment managers’ contemplating investment in green rather than gray infrastructure.
Despite the lack of formal guidance on comparing green with gray infrastructure, the general contour of a standardised GGA methodology emerges from a mix of economic decision theory, portfolio theory, public investment theory, non-market valuation and a growing list of applied case studies.
For example, federal analysts considering the best alternatives for configuring ports, highways, dams and other major public infrastructure investments are already well steeped in social benefit-cost analysis (BCA) where long-term returns to society in the form of improved navigation, flood control, or transportation savings are compared with capital, maintenance and operations costs.
Green infrastructure presents another alternative that is typically overlooked, but which can nonetheless be compared – albeit with some added complexity – to these more conventional alternatives using standard methods of BCA. Drawing on these tools, we were able to distill six key components for an effective general methodology, which we then tested in Portland, Maine:
First, the investment objective and constraints must be very clearly specified. Although intuitive, this step is essential for getting the math right, which involves making sure all relevant benefits and costs are included in the right units, and in the right places in the investment trade-off equations. Small computational errors – such as neglecting to annualise capital investments over the proper length of time – can have huge implications for the feasibility of either green or gray options.
Specifying the investment objective in mathematical terms minimises the probability of such errors occurring. GGA is a special case of public investment limited to situations where environmental outcomes are sought and where both gray and green infrastructure options exist.
A survey of existing case studies and potential applications suggests that most green-gray analyses fall into one of three distinct investment objectives. Each of these objectives can be expressed by mathematical formulas familiar to investment managers and used for selecting the optimal investment portfolio when a diversity of options exists.
Second, portfolios that include both green and gray investments must be developed. In each infrastructure investment situation, there may be one or more gray, and likely several green, investment options under consideration. Developing a portfolio of gray options is fairly straightforward, as technologies are relatively well understood. There is less familiarity with green options, although the literature on the number and applicability of various green infrastructure solutions is rapidly evolving.
In constructing green portfolios, there are several unique aspects to consider, such as physical constraints (for example, there are only so many streams where riparian buffers could be restored); the need to incorporate redundancy (for example, replanting two acres of trees instead of one in case one burns down); and sequencing (for example, obtaining water rights before constructing wetlands). A more complete GGA methodology would provide practical guidance on all of the unique aspects of green portfolio design.
Third, the outcomes must be clearly modelled. This is perhaps the trickiest aspect of GGA. Quantitatively establishing the relationship between the level of investment in any one green infrastructure project and the environmental outcomes requires careful modeling that relates changes in ecosystem function to changes in economic services provided. As one example, there has been considerable work relating wetland acreage to associated maximum storm surge heights and associated losses.
While gray infrastructure like water treatment plant depreciates in value over time, many green assets appreciate in value [EPA]
On the other, there has been almost no work at all relating installation of green storm water controls to reductions in nitrogen or phosphorous runoff – most studies have focused on volume reductions. In these situations, the trickiest step is making assumptions about the relationship when there is little scientific information to go on.
Fourth, present-value costs and benefits of individual green and gray measures must be quantified. Before portfolios of green or gray options are considered, each individual component needs to be analysed by itself. An important consideration in GGA is to ensure that both green and gray options are analysed on a common platform so that costs and benefits can be directly compared or combined.
The gray infrastructure option should serve as the baseline since GGA is often considered in contrast to some impending gray investment decision, and not vice versa. Adopting gray as the baseline requires evaluation of green options within the general analytical framework offered by standard infrastructure investment methods.
The US Environmental Protection Agency provides a useful synopsis of standard two-stage discounting to evaluate gray infrastructure investments. Present-value costs and benefits of green infrastructure can be modeled in precisely the same way, albeit with a few complexities.
Fifth, and at the heart of GGA, is using alternative investment analysis to compare green against gray, or different combinations of green and gray together. Once the benefits and costs of individual green or gray measures are calculated, the next step is then to compare full investment portfolios. Depending on the investment objective, this comparison is carried out by using either benefit-cost analysis (BCA) or cost-effectiveness analysis.
BCA is a technique that is used to estimate and sum up the future flows of benefits and costs given particular resource allocation or policy decisions. Based on this sum, the value of a particular choice can be compared against some set of alternatives. Cost-effectiveness analysis on the other hand is a technique for identifying the least-cost option for meeting a specific physical outcome.
Finally, one must account for risk and uncertainty. Many believe that green infrastructure investments are generally riskier and more uncertain than gray. But gray is also subject to significant risks, such as plans for maintenance that are never carried out and technological failures that occur all too frequently.
Nonetheless, sources of risk unique to green include the possibilities of floods, fires, insect outbreaks, extreme drought and climate change to significantly affect the function of green infrastructure elements over the long run. Sources of uncertainty include poor existing data on implementation costs, speculative relationships between green infrastructure elements and the environmental outcome sought, and lack of understanding about important land-use trends, market trends, landowner behaviour, or policy changes that have bearing on the investment decision.
Risk and uncertainty can be dealt with in two fundamental ways – through project design and through project analysis. Redundancy, or having two or more green infrastructure elements included to achieve the same outcome, is one way to reduce risk and uncertainty in the design of green infrastructure investment portfolios. With respect to analysis, standard approaches for incorporating risk and uncertainty include sensitivity analysis, scenarios, and use of expected values.
Portland Water District case study
Drawing on these six components, we conducted a case study of the Sebago Lake Watershed in the Portland Water District in Maine (PWD). Sebago Lake contains some of the cleanest water in the Northeastern United States and is also the primary drinking-water source for PWD, supplying drinking water to over 200,000 people daily.
PWD currently qualifies for filtration avoidance under the US Environmental Protection Agency 1989 Surface Water Treatment Rule (SWTR). The rule waives public water systems from requirements to install filtration systems as long as concentrations of turbidity and either fecal or total coliform are maintained at or below regulatory baselines through upstream land-use management practices.
In recent years, concerns have been expressed that upstream development, deforestation, and population growth trends may jeopardise the filtration waiver and force PWD to install a conventional filtration system. For example, the US Forest Service has determined that certain areas of the Sebago Lake watershed are at high risk of forest conversion due to development pressure, which, coupled with unsustainable land use practices, are a major threat to water quality.
In response, commercial water users, residents, non-governmental organisations, recreation interests and other stakeholders are actively investigating green infrastructure alternatives that would minimise the chance of losing the waiver and otherwise help reduce PWD’s water treatment costs. Using the GGA methods discussed above, we completed a preliminary analysis to provide an initial sense of the economic trade-offs involved and to identify the various data gaps and parameters that would need to be addressed for a more complete analysis.
Using cost-effectiveness analysis for our framework, we compared the costs of a new filtration plant with investment in six green infrastructure elements over the next 20 years that together would help maintain the watershed’s high-quality waters. These included riparian buffers, upgrades to culverts, sustainability certification of future timber harvests, reforestation and conservation easements.
The quantity available and costs associated with the green infrastructure portfolio were determined through on-site consultations throughout the watershed, review of publicly available data and GIS analysis.
|A recent analysis by New York City found that green roofs could save $1bn in helping to meet water-quality goals [Reuters]|
We ran six scenarios that represented different levels of investment, analysis periods, assumptions regarding the efficacy of green infrastructure measures, cost assumptions, and discount rates. Our key findings include:
1. The present-value life-cycle cost of building a new filtration plant would range from $97 to $155m across the scenarios.
2. The present-value life-cycle cost of green infrastructure solutions range from $44 to $172m across the scenarios.
3. Under four scenarios, green infrastructure represented a cost savings, with the most optimistic case of $111m saved over 20 years.
4. Under two scenarios, gray infrastructure proved superior. Under the least optimistic for green, green infrastructure would represent a 44 percent increase in costs.
5. Uncertainty over green infrastructure efficacy and costs are what accounted for the wide range of outcomes across the modeled scenarios.
6. Ancillary benefits in the form of carbon sequestration and Atlantic salmon habitat would make an even more compelling case for investment in green infrastructure. By combining empirical data on the ground with calibrated nonmarket benefits transferred from other settings, we estimate that these nonmarket benefits would amount to $72 to $125m over a 20-year timeframe. Including these ancillary benefits would make green infrastructure superior in all six scenarios.
Towards more widespread and robust applications of GGA
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 (for example, a green multi-barrier approach), analytical adjustments (for example, modelling 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 standardised 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.
Erin Gray is a research associate for the World Resources Institute in Washington, DC. Her current research focuses on natural resource valuation, green infrastructure, regreening and watershed development, and climate change adaptation.
Logan Yonavjak is assistant manager for the Conservation Investment Note Program, where she is working with a group of conservation finance professionals to set up a new investment vehicle for land conservation and rural economic development in the United States.
Dr John Talberth is a senior economist with World Resources Institute (WRI) in Washington, DC, and president of Center for Sustainable Economy. At WRI, he co-ordinates economic analysis for projects across the institute addressing climate adaptation, nutrient trading, forest conservation and international sustainable development.
Todd Gartner is a senior associate for the World Resources Institute’s People and Ecosystems Program. He focuses on developing new ways to finance conservation though the use of conservation incentives and market-based strategies, such as habitat mitigation and payments for source water protection. His previous work included developing the Conservation Incentives program at the American Forest Foundation, fire ecology and eco-tourism research, and several years as a corporate financial consultant.
A version of this article first appeared on the Solutions Journal.