Rural and forest fires represent one of the most significant sources of emissions in the atmosphere of trace gases and aerosol particles, which significantly impact carbon budget, air quality, and human health. This paper aims to illustrate an integrated modelling approach combining spatial and non-spatial inputs to provide and enhance the estimation of GHG and particulate matter emissions from surface fires using Italy as a case study over the period 2007-2017. Three main improvements characterize the approach proposed in this work: (i) the collection and development of comprehensive and accurate data inputs related to burned area; (ii) the use of the most recent data on fuel type and load; and (iii) the modelling application to estimate fuel moisture, burning efficiency, and fuel consumption considering meteorological factors and combustion phases. On average, Italy's GHG and particulate matter emissions were 2621 Gg yr 1, ranging from a minimum of 772 Gg yr-; 1 in 2013 to a maximum of 7020 Gg yr13; 1 in 2007. Emissions from fire disturbances in broadleaf forests, shrublands, and agricultural fuel types account for about 76 % of the total. Results were compared with global and national inventories and showed good agreement, especially considering CO2 and particulate matter. The approach of this study added confidence in emission estimates, and the results can be utilized in decision support systems to address air quality management and fire impact mitigation policies.
Estimating annual GHG and particulate matter emissions from rural and forest fires based on an integrated modelling approach / Scarpa, C.; Bacciu, V.; Ascoli, D.; Costa-Saura, J. M.; Salis, M.; Sirca, C.; Marchetti, M.; Spano, D.. - In: SCIENCE OF THE TOTAL ENVIRONMENT. - ISSN 1879-1026. - 907:(2024). [10.1016/j.scitotenv.2023.167960]
Estimating annual GHG and particulate matter emissions from rural and forest fires based on an integrated modelling approach
Scarpa C.;Costa-Saura J. M.;Sirca C.;Spano D.
2024-01-01
Abstract
Rural and forest fires represent one of the most significant sources of emissions in the atmosphere of trace gases and aerosol particles, which significantly impact carbon budget, air quality, and human health. This paper aims to illustrate an integrated modelling approach combining spatial and non-spatial inputs to provide and enhance the estimation of GHG and particulate matter emissions from surface fires using Italy as a case study over the period 2007-2017. Three main improvements characterize the approach proposed in this work: (i) the collection and development of comprehensive and accurate data inputs related to burned area; (ii) the use of the most recent data on fuel type and load; and (iii) the modelling application to estimate fuel moisture, burning efficiency, and fuel consumption considering meteorological factors and combustion phases. On average, Italy's GHG and particulate matter emissions were 2621 Gg yr 1, ranging from a minimum of 772 Gg yr-; 1 in 2013 to a maximum of 7020 Gg yr13; 1 in 2007. Emissions from fire disturbances in broadleaf forests, shrublands, and agricultural fuel types account for about 76 % of the total. Results were compared with global and national inventories and showed good agreement, especially considering CO2 and particulate matter. The approach of this study added confidence in emission estimates, and the results can be utilized in decision support systems to address air quality management and fire impact mitigation policies.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.