Dataset supporting the estimation and analysis of high spatial resolution inventories of atmospheric emissions from several sectors in Argentina
Salvador Enrique Puliafito,
Tomás Rafael Bolaño-Ortiz,
Lucas Luciano Berná Peña,
Romina María Pascual-Flores
Affiliations
Salvador Enrique Puliafito
GEAA - Grupo de Estudios Atmosféricos y Ambientales, UTN-FRM - Universidad Tecnológica Nacional - Facultad Regional Mendoza, Mendoza, Argentina; CONICET - Consejo Nacional de Investigaciones Científicas y Técnicas, Buenos Aires, Argentina; Corresponding author. GEAA - Grupo de Estudios Atmosféricos y Ambientales, UTN-FRM - Universidad Tecnológica Nacional - Facultad Regional Mendoza, Mendoza, Argentina.
Tomás Rafael Bolaño-Ortiz
GEAA - Grupo de Estudios Atmosféricos y Ambientales, UTN-FRM - Universidad Tecnológica Nacional - Facultad Regional Mendoza, Mendoza, Argentina; CONICET - Consejo Nacional de Investigaciones Científicas y Técnicas, Buenos Aires, Argentina
Lucas Luciano Berná Peña
GEAA - Grupo de Estudios Atmosféricos y Ambientales, UTN-FRM - Universidad Tecnológica Nacional - Facultad Regional Mendoza, Mendoza, Argentina; ANPCyT - Agencia Nacional de Promoción Científica y Tecnológica, Buenos Aires, Argentina
Romina María Pascual-Flores
GEAA - Grupo de Estudios Atmosféricos y Ambientales, UTN-FRM - Universidad Tecnológica Nacional - Facultad Regional Mendoza, Mendoza, Argentina; CONICET - Consejo Nacional de Investigaciones Científicas y Técnicas, Buenos Aires, Argentina
This data article provides an extensive and complete description of the high spatial resolution inventory (HSRI) estimation shown in the article “High resolution inventory of atmospheric emissions from livestock production, agriculture, and biomass burning sectors of Argentina” Puliafito et al. [1], and its comparison with several sectors in Argentina. The dataset provided are high-resolution inventories (0.025° × 0.025° lat/long) for CO2, CH4, N2O and another 8 species from livestock, biomass burning, agriculture and another 12 sectors (based on 2016 year). In addition, we also provide the database for 2014 using the same methodology. The dataset presented are necessary to improve input inventories for air quality models. Also, they are better to inform and guide the stakeholders, in making decisions related to environmental protection and health promotion, as well as assessing the environmental performance in terms of atmospheric emissions of an activity, sector or region in Argentina. Keywords: Air quality model, High-resolution emissions inventory, Greenhouse gas, Methane, Energy, Livestock production, Agriculture, Biomass burning