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What drives the location and diffusion of biogas units?

Author

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  • Martin Faulques

    (CREM - Centre de recherche en économie et management - UNICAEN - Université de Caen Normandie - NU - Normandie Université - UR - Université de Rennes - CNRS - Centre National de la Recherche Scientifique, UNICAEN - Université de Caen Normandie - NU - Normandie Université)

Abstract

In recent years, biogas units have become an important component of the energy transition, capable of converting waste and biomass into biogas. However, location is influenced by the efficiency and profitability of these biogas units. Previous research has focused on the economic, social, political, and environmental criteria for the siting of biogas units. Furthermore, studies have shown a tendency for co-location of eco-innovations, primarily due to the proximity of resources and the exchange of technical knowledge among neighbouring units (mimicry effects). However, this proximity can also lead to increased competition for local resources, potentially undermining the collective efficiency of the installations. This article aims to understand this paradox by exploring how the geographical proximity between units influences the siting of biogas units in the Brittany and Normandy regions. Using a Spatial Durbin model, we have examined the interactions between units and how these dynamics influence the factors affecting the probability of unit installation. Our results show that there are clusters of biogas units extending over approximately 17 kilometres. However, these effects are spatially limited: when the units are too close, competition for resources limits their installations, while when they are too far apart, the effect disappears.

Suggested Citation

  • Martin Faulques, 2025. "What drives the location and diffusion of biogas units?," Working Papers hal-04839529, HAL.
  • Handle: RePEc:hal:wpaper:hal-04839529
    Note: View the original document on HAL open archive server: https://hal.science/hal-04839529v1
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    More about this item

    Keywords

    Biogas units; Spatial Durbin Model; Proximity; Methane potentials; Location C31; R12; 013; Q4;
    All these keywords.

    JEL classification:

    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • R12 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Size and Spatial Distributions of Regional Economic Activity; Interregional Trade (economic geography)
    • Q4 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy

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