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Erschienen in: Clean Technologies and Environmental Policy 4/2014

01.04.2014 | Original Paper

Assessing sustainability when data availability limits real-time estimates: using near-time indicators to extend sustainability metrics

verfasst von: Matthew T. Heberling, Matthew E. Hopton

Erschienen in: Clean Technologies and Environmental Policy | Ausgabe 4/2014

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Abstract

The goal of this paper is to highlight the problem of time lags in data releases that are necessary for calculating sustainability metrics and its effect on making informed management decisions. We produced a methodology to assess whether a regional system is on a sustainable path and tested it in south-central Colorado. We identified key components of the system and selected four sustainability metrics that measure those components. Metrics included: (1) ecological footprint (i.e., environmental burden), (2) green net regional product (GNRP) (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 limitation was the delay between when an event occurred and when data on the event were released. Given, the recent push in government agencies for calculating sustainability metrics, finding solutions for the time lag will be important. To address this limitation, we explore the potential of using both sustainability metrics and indicators that are available near-time to provide decision makers with better decision support. For the pilot study in Colorado, the metric calculations were 3 years behind present. 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 correlated with ecological balance (a component of ecological footprint) and GNRP. We use Spearman rank correlations and scatter plots to identify the relationship of the metrics and near-time indicators in an exploratory analysis. We offer research recommendations to consider.

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Fußnoten
1
For clarification, we distinguish between “metric” or “index,” and “indicator.” Mayer (2008) defines an indicator as measuring one characteristic or variable (e.g., CO2 emissions), but an index combines many indicators or variables through aggregation (e.g., ecological footprint). Therefore, indices can provide a multidimensional view of sustainability and are capable of quantifying the condition of an entire system. For this paper, metric and index are synonymous.
 
2
We state there was a three-year lag for the original study, which was based primarily on CO2 emissions data. For this particular variable, a new approach for these emissions data was under consideration (pers. comm., P. Lindstrom 2008). As Table 1 points out, CO2 emissions now have a 2-year delay.
 
3
StatSoft, Inc. (2011). STATISTICA (data analysis software system), version 10. www.​statsoft.​com.
 
4
Typically, population estimates for counties through July of a given year are available in December of that year and annual estimates are released in April of the following year. Because of the decadal census, county estimates for 2010 were released March 2011.
 
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Metadaten
Titel
Assessing sustainability when data availability limits real-time estimates: using near-time indicators to extend sustainability metrics
verfasst von
Matthew T. Heberling
Matthew E. Hopton
Publikationsdatum
01.04.2014
Verlag
Springer Berlin Heidelberg
Erschienen in
Clean Technologies and Environmental Policy / Ausgabe 4/2014
Print ISSN: 1618-954X
Elektronische ISSN: 1618-9558
DOI
https://doi.org/10.1007/s10098-013-0683-6

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