Social and environmental conflict analysis on energy projects: Bayesian predictive network approach
Por:
Hernandez-Cedeno, Isaac, Nelson, Pamela F., Angles-Hernandez, Marisol
Publicada:
1 oct 2021
Resumen:
This paper analyzes the social and environmental aspects of energy and
large-scale projects through the use of Bayesian Networks. To do this, a
database was created that includes conflict causes related to 267
projects in Mexico with 12 well-defined and orthogonal social and
environmental conflict causes. These are lack of information and
participation, fear of change to local communities, health and
environmental damage, reduction of primary sector activities, proximity
to cultural landmarks, employee dissatisfaction, political interests,
violence to the community, water use, non-compliance of agreements, land
use disputes, and others not defined. The database was the input for two
Bayesian Networks, network ``A'' estimates the likelihood of approval
or risk of suspension of a project because of the conflict causes, with
an overall accuracy of 80.3%. The network ``B'' estimates the costs
of conflictive situations and how likely they can be resolved by adding
benefits. A sensitivity analysis found that five conflict causes can
reduce the probability of a project's success by 10-39%. Finally,
policy implications were identified, resulting in four recommendations
for implementation in national regulations. The tools developed here
enable measurement of the benefits of energy projects, provide
policymakers tools to improve public decisions, and help avoid
conflicts.
Filiaciones:
Hernandez-Cedeno, Isaac:
Hernandez-Cedeno, I (Corresponding Author), Univ Nacl Autonoma Mexico, Fac Engn, Energy Syst Dept, Circuito Escolar S-N, Mexico City 04510, DF, Mexico. Hernandez-Cedeno, Isaac
Angles-Hernandez, Marisol:
Hernandez-Cedeno, I (Corresponding Author), Univ Nacl Autonoma Mexico, Fac Engn, Energy Syst Dept, Circuito Escolar S-N, Mexico City 04510, DF, Mexico. Hernandez-Cedeno, Isaac
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