This paper explores the social impact for population in the energy sector combining LCA and SIA (social impact assessment). As case study, a new 66 MW wind power plant under development in the countryside of Southern Sardinia has been considered. The innovative method, based on the analysis of the context, aims to empirically analyze some selected sustainability indicators. The proposed method starts from a detailed analysis of the wind power project, with particular reference to the plant site characteristics, technical features of the wind farm, opinions of the stakeholders, environmental and social impacts and expected economic benefits. The acquired data are validated with a Severity statistical method that identifies the KPIs. The indicators are classified into general categories of damage Human life, Safety guarantee, Social resources, Public participation and analyzed through a combined SIA-LCA method to identify indicators damage weights. This work shows the importance of putting together indicators already explored in the environmental field such as Human health, Ecosystem quality, Resource, Climate Change and as social indicators Renewable Energy with Noise, Visual Impact, Shadow Flichers, the perceptions of the local community.
Social impact assessment of wind power generation. An innovative method for decision making processes
Valeria Fois
;Lorenzo Lecis;Daniele Cocco
2022-01-01
Abstract
This paper explores the social impact for population in the energy sector combining LCA and SIA (social impact assessment). As case study, a new 66 MW wind power plant under development in the countryside of Southern Sardinia has been considered. The innovative method, based on the analysis of the context, aims to empirically analyze some selected sustainability indicators. The proposed method starts from a detailed analysis of the wind power project, with particular reference to the plant site characteristics, technical features of the wind farm, opinions of the stakeholders, environmental and social impacts and expected economic benefits. The acquired data are validated with a Severity statistical method that identifies the KPIs. The indicators are classified into general categories of damage Human life, Safety guarantee, Social resources, Public participation and analyzed through a combined SIA-LCA method to identify indicators damage weights. This work shows the importance of putting together indicators already explored in the environmental field such as Human health, Ecosystem quality, Resource, Climate Change and as social indicators Renewable Energy with Noise, Visual Impact, Shadow Flichers, the perceptions of the local community.File | Dimensione | Formato | |
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