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Assessing Sustainability When Data Availability Limits Real-Time Estimates: Using Near-Time Indicators to Extend Sustainability Metrics
HEBERLING, M. T. AND M. E. HOPTON. Assessing Sustainability When Data Availability Limits Real-Time Estimates: Using Near-Time Indicators to Extend Sustainability Metrics. CLEAN TECHNOLOGIES AND ENVIRONMENTAL POLICY. Springer Berlin-Heidelberg, , Germany, 16(4):739-748, (2014).
We produced a scientifically defensible methodology to assess whether a regional system is on a sustainable path. The approach required readily available data, metrics applicable to the relevant scale, and results useful to decision makers. We initiated a pilot project to test the methodology in south-central Colorado. We identified key components of the system and selected four sustainability metrics that quantify those components. Metrics included: 1) Ecological Footprint (i.e., environmental burden), 2) Green Net Regional Product (i.e., economic well-being), 3) Emergy (i.e., energy flows), and 4) Fisher information (i.e., dynamic order). Having calculated these metrics, we identified future research recommendations and limitations. One drawback was a delay between when an event occurred and when data on the event were released. Given the recent push for calculating sustainability metrics in government agencies, finding solutions for the time lag will be important. To address this limitation, we explore the potential of using both sustainability metrics and near-time indicators of sustainability to provide decision makers with better decision support. The sustainability metrics had a time lag because not all of the necessary data were available to calculate the current year, and the calculations were three years behind the present year. Using near-time indicators that are publicly available before the metrics can be calculated might help to predict the path of the metric. As an example, we examine if specific near-time indicators are related to Ecological Footprint and Green Net Regional Product, two lagging measures. We use Spearman rank correlations and create scatter plots to identify the relationship of the metrics and near-time indicators in an exploratory analysis. Although we identify potential leading indicators, we offer research recommendations to consider.
To inform the public
Record Details:Record Type: DOCUMENT (JOURNAL/PEER REVIEWED JOURNAL)
Organization:U.S. ENVIRONMENTAL PROTECTION AGENCY
OFFICE OF RESEARCH AND DEVELOPMENT
NATIONAL RISK MANAGEMENT RESEARCH LABORATORY
SUSTAINABLE TECHNOLOGY DIVISION
SUSTAINABLE ENVIRONMENTS BRANCH