in the system by a sphere (see bottom left panel in Fig. 1). To avoid overcrowding,
we load only a few spheres onto the plane at a time. In a first step, we associate each
user with a k-dimensional vector: one entry corresponding to each response to the
assessment questions. We then apply PCA to the set of vectors and the algorithm
returns a two dimensional (x, y) location for each participant. This point corresponds to the top 2 eigenvectors of the covariance matrix. We then center the
visualization on the user’s (xp, yp) position, and then arrange the spheres in the new
coordinate space. Spheres in closer proximity represent users who responded to the
assessment questions similarly. This allows users to immediately see how people
similar to them feel about what issues should be considered when developing an
energy portfolio. Spheres that are larger in size represent users whose suggestion
has been rated as highly important by others.
3 Evaluation Metrics
The metrics that we will use to gauge public perception of energy and its sources
must be familiar to the general public rather than technical. At the same time the
significance and relevance of such metrics will be guaranteed following a
well-established framework. The United Nations World Commission on
Environment and Development (WCED) in the 1987 defined sustainable development as the “development that meets the needs of the present without compromising the ability of future generations to meet their own needs.” [1] A typical
framework, empowering this definition is the “Triple Bottom Line” [2]. The Triple
Bottom Line (3BL) is a framework, well established in the scientific literature as
well as public-oriented publications, with three key elements: social, environmental
(or ecological) and economics. It provides a holistic perspective to assess the
sustainability of several engineering solutions. A state-of-the-art framework to
assess the sustainability of power plants and their life cycle (nuclear in particular) is
provided in [3]. Regarding environmental indicators in particular, the US EPA has
focused on determining and developing the best impact assessment tool for Life
Cycle Impact Assessment (LCIA), Pollution Prevention (P2), and Sustainability
Metrics for the US. This research led to the creation of TRACI—the Tool for the
Reduction and Assessment of Chemical and other environmental Impacts. The
methodology has been developed specifically for the US using input parameters
consistent with US locations. Site specificity is available for many of the impact
categories, but in all cases a US average value exists when the location is undetermined. The average values were implemented in the ecoinvent data. Further
information is available at http://www.epa.gov/nrmrl/std/traci/traci.html. TRACI is
therefore useful to compare different power plants and their life cycle.
Unfortunately, these frameworks are hardly compressive for non-experts. In particular regarding the power sectors, people often have misconceptions that the tool
envisaged by this research program will contribute to overcome. Some of the most
relevant examples that we will address are:
130
M. Fratoni et al.
we load only a few spheres onto the plane at a time. In a first step, we associate each
user with a k-dimensional vector: one entry corresponding to each response to the
assessment questions. We then apply PCA to the set of vectors and the algorithm
returns a two dimensional (x, y) location for each participant. This point corresponds to the top 2 eigenvectors of the covariance matrix. We then center the
visualization on the user’s (xp, yp) position, and then arrange the spheres in the new
coordinate space. Spheres in closer proximity represent users who responded to the
assessment questions similarly. This allows users to immediately see how people
similar to them feel about what issues should be considered when developing an
energy portfolio. Spheres that are larger in size represent users whose suggestion
has been rated as highly important by others.
3 Evaluation Metrics
The metrics that we will use to gauge public perception of energy and its sources
must be familiar to the general public rather than technical. At the same time the
significance and relevance of such metrics will be guaranteed following a
well-established framework. The United Nations World Commission on
Environment and Development (WCED) in the 1987 defined sustainable development as the “development that meets the needs of the present without compromising the ability of future generations to meet their own needs.” [1] A typical
framework, empowering this definition is the “Triple Bottom Line” [2]. The Triple
Bottom Line (3BL) is a framework, well established in the scientific literature as
well as public-oriented publications, with three key elements: social, environmental
(or ecological) and economics. It provides a holistic perspective to assess the
sustainability of several engineering solutions. A state-of-the-art framework to
assess the sustainability of power plants and their life cycle (nuclear in particular) is
provided in [3]. Regarding environmental indicators in particular, the US EPA has
focused on determining and developing the best impact assessment tool for Life
Cycle Impact Assessment (LCIA), Pollution Prevention (P2), and Sustainability
Metrics for the US. This research led to the creation of TRACI—the Tool for the
Reduction and Assessment of Chemical and other environmental Impacts. The
methodology has been developed specifically for the US using input parameters
consistent with US locations. Site specificity is available for many of the impact
categories, but in all cases a US average value exists when the location is undetermined. The average values were implemented in the ecoinvent data. Further
information is available at http://www.epa.gov/nrmrl/std/traci/traci.html. TRACI is
therefore useful to compare different power plants and their life cycle.
Unfortunately, these frameworks are hardly compressive for non-experts. In particular regarding the power sectors, people often have misconceptions that the tool
envisaged by this research program will contribute to overcome. Some of the most
relevant examples that we will address are:
130
M. Fratoni et al.