Development of a Model to Estimate the Risk of Emission of Greenhouse Gases from Forest Fires
Victoria Lerma-Arce,
Celia Yagüe-Hurtado,
Helena Van den Berg,
Miguel García-Folgado,
Jose-Vicente Oliver-Villanueva,
Yacine Benhalima,
Inês Marques-Duarte,
Vanda Acácio,
Francisco C. Rego,
Eduardo López-Senespleda,
María Menéndez-Miguélez,
Ricardo Ruiz-Peinado,
Thomas Petillon,
Stéphanie Jalabert,
Ester Carbó-Valverde,
Eugenia Gimeno-García,
Rebeca Aleix-Amurrio,
Edgar Lorenzo-Sáez
Affiliations
Victoria Lerma-Arce
Institute of Information and Communication Technologies (ITACA), Universitat Politècnica de València (UPV), Camino de Vera s/n, 46022 Valencia, Spain
Celia Yagüe-Hurtado
Institute of Information and Communication Technologies (ITACA), Universitat Politècnica de València (UPV), Camino de Vera s/n, 46022 Valencia, Spain
Helena Van den Berg
Institute of Information and Communication Technologies (ITACA), Universitat Politècnica de València (UPV), Camino de Vera s/n, 46022 Valencia, Spain
Miguel García-Folgado
Institute of Information and Communication Technologies (ITACA), Universitat Politècnica de València (UPV), Camino de Vera s/n, 46022 Valencia, Spain
Jose-Vicente Oliver-Villanueva
Institute of Information and Communication Technologies (ITACA), Universitat Politècnica de València (UPV), Camino de Vera s/n, 46022 Valencia, Spain
Yacine Benhalima
InBio, Centro de Ecologia Aplicada “Professor Baeta Neves”, Instituto Superior de Agronomia, Universidade de Lisboa, Tapada da Ajuda, 1349-017 Lisbon, Portugal
Inês Marques-Duarte
InBio, Centro de Ecologia Aplicada “Professor Baeta Neves”, Instituto Superior de Agronomia, Universidade de Lisboa, Tapada da Ajuda, 1349-017 Lisbon, Portugal
Vanda Acácio
InBio, Centro de Ecologia Aplicada “Professor Baeta Neves”, Instituto Superior de Agronomia, Universidade de Lisboa, Tapada da Ajuda, 1349-017 Lisbon, Portugal
Francisco C. Rego
InBio, Centro de Ecologia Aplicada “Professor Baeta Neves”, Instituto Superior de Agronomia, Universidade de Lisboa, Tapada da Ajuda, 1349-017 Lisbon, Portugal
Eduardo López-Senespleda
Instituto de Ciencias Forestales (ICIFOR-INIA), CSIC, 28040 Madrid, Spain
María Menéndez-Miguélez
Instituto de Ciencias Forestales (ICIFOR-INIA), CSIC, 28040 Madrid, Spain
Ricardo Ruiz-Peinado
Instituto de Ciencias Forestales (ICIFOR-INIA), CSIC, 28040 Madrid, Spain
Thomas Petillon
Bordeaux Science Agro, UMR CNRS 5805 EPOC, 1 cours du Général De Gaulle, 33175 Gradignan, France
Stéphanie Jalabert
Bordeaux Science Agro, UMR CNRS 5805 EPOC, 1 cours du Général De Gaulle, 33175 Gradignan, France
Ester Carbó-Valverde
Department of Environmental Quality and Soils, Centro de Investigaciones sobre Desertificación—CIDE (CSIC-Universitat de Valencia-GV), 46113 Valencia, Spain
Eugenia Gimeno-García
Department of Environmental Quality and Soils, Centro de Investigaciones sobre Desertificación—CIDE (CSIC-Universitat de Valencia-GV), 46113 Valencia, Spain
Rebeca Aleix-Amurrio
Asociación de Municipios Forestales de la Comunitat Valenciana (AMUFOR), 46810 Valencia, Spain
Edgar Lorenzo-Sáez
Institute of Information and Communication Technologies (ITACA), Universitat Politècnica de València (UPV), Camino de Vera s/n, 46022 Valencia, Spain
While the Mediterranean basin is foreseen to be highly affected by climate change (CC) and severe forest fires are expected to be more frequent, international efforts to fight against CC do not consider forest fires’ greenhouse gas (GHG) emissions risk and the possibility of its mitigation. This is partly due to a lack of a methodology for GHG risk spatial assessment and consideration of the high value of carbon stocks in forest ecosystems and their intrinsic risk. To revert this, an innovative GHG emission risk model has been developed and implemented in a pilot forest area. This model considers geospatial variables to build up emission vulnerability based on potential fire severity and resistance of a landscape, value at risk and the hazard of a fire occurrence. The results classify low, moderate and high emission risks in the analysed areas. This identification of hotspots allows the prioritisation of fire prevention measures in a region to maximise the reduction of GHG emissions in the case of a fire event. This constitutes the first step in a holistic and consistent CC mitigation that not only considers anthropic GHG sources but also possible GHG emissions by forest fires that can be actively prevented, managed and reduced.
