Development of a Model to Estimate the Risk of Emission of Greenhouse Gases from Forest Fires

Author:

Lerma-Arce Victoria1ORCID,Yagüe-Hurtado Celia1ORCID,Van den Berg Helena1,García-Folgado Miguel1ORCID,Oliver-Villanueva Jose-Vicente1ORCID,Benhalima Yacine23,Marques-Duarte Inês2ORCID,Acácio Vanda2ORCID,Rego Francisco2,López-Senespleda Eduardo4ORCID,Menéndez-Miguélez María4ORCID,Ruiz-Peinado Ricardo4ORCID,Petillon Thomas5,Jalabert Stéphanie5,Carbó-Valverde Ester6ORCID,Gimeno-García Eugenia6ORCID,Aleix-Amurrio Rebeca7,Lorenzo-Sáez Edgar1ORCID

Affiliation:

1. Institute of Information and Communication Technologies (ITACA), Universitat Politècnica de València (UPV), Camino de Vera s/n, 46022 Valencia, Spain

2. InBio, Centro de Ecologia Aplicada “Professor Baeta Neves”, Instituto Superior de Agronomia, Universidade de Lisboa, Tapada da Ajuda, 1349-017 Lisbon, Portugal

3. Associated Laboratory TERRA, LEAF—Linking Landscape, Environment, Agriculture and Food—Research Center, Instituto Superior de Agronomia, Universidade de Lisboa, Tapada da Ajuda, 1349-017 Lisbon, Portugal

4. Instituto de Ciencias Forestales (ICIFOR-INIA), CSIC, 28040 Madrid, Spain

5. Bordeaux Science Agro, UMR CNRS 5805 EPOC, 1 cours du Général De Gaulle, 33175 Gradignan, France

6. Department of Environmental Quality and Soils, Centro de Investigaciones sobre Desertificación—CIDE (CSIC-Universitat de Valencia-GV), 46113 Valencia, Spain

7. Asociación de Municipios Forestales de la Comunitat Valenciana (AMUFOR), 46810 Valencia, Spain

Abstract

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.

Funder

REMAS project

Interreg Sudoe Programme through the European Regional Development Fund

Publisher

MDPI AG

Subject

Earth and Planetary Sciences (miscellaneous),Safety Research,Environmental Science (miscellaneous),Safety, Risk, Reliability and Quality,Building and Construction,Forestry

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