This study presents a 2014 high-resolution spatially disaggregated emission inventory (0.025° × 0.025° horizontal resolution), of the main activities in the energy sector in Argentina. The sub-sectors considered are public generation of electricity, oil refineries, cement production, transport (maritime, air, rail and road), residential and commercial. The following pollutants were included: greenhouse gases (CO2, CH4, N2O), ozone precursors (CO, NOx, VOC) and other specific air quality indicators such as SO2, PM10, and PM2.5. This work could contribute to a better geographical allocation of the pollutant sources through census based population maps. Considering the sources of greenhouse gas emissions, the total amount is 144 Tg CO2eq, from which the transportation sector emits 57.8 Tg (40%); followed by electricity generation, with 40.9 Tg (28%); residential + commercial, with 31.24 Tg (22%); and cement and refinery production, with 14.3 Tg (10%). This inventory shows that 49% of the total emissions occur in rural areas: 31% in rural areas of medium population density, 13% in intermediate urban areas and 7% in densely populated urban areas. However, if emissions are analyzed by extension (per square km), the largest impact is observed in medium and densely populated urban areas, reaching more than 20.3 Gg per square km of greenhouse gases, 297 Mg/km2 of ozone precursors gases and 11.5 Mg/km2 of other air quality emissions. A comparison with the EDGAR global emission database shows that, although the total country emissions are similar for several sub sectors and pollutants, its spatial distribution is not applicable to Argentina. The road and residential transport emissions represented by EDGAR result in an overestimation of emissions in rural areas and an underestimation in urban areas, especially in more densely populated areas. EDGAR underestimates 60 Gg of methane emissions from road transport sector and fugitive emissions from refining activities.

This work studied the spread of COVID-19, the meteorological conditions and the air quality in a megacity from two viewpoints: (1) the correlation between meteorological and air quality (PM₁₀ and NO₂) variables with infections and deaths due COVID-19, and (2) the improvement in air quality. Both analyses were performed for the pandemic lockdown due to COVID-19 in the City of Buenos Aires (CABA), the capital and the largest city in Argentina. Daily data from temperature, rainfall, average relative humidity, wind speed, PM₁₀, NO₂, new cases and deaths due COVID-19 were analyzed. Our findings showed a significant correlation of meteorological and air quality variables with COVID-19 cases. The highest temperature correlation occurred before the confirmation day of new cases. PM₁₀ presented the highest correlation within 13 to 15 days lag, while NO₂ within 3 to 6 days lag. Also, reductions in PM₁₀ and NO₂ were observed. This study shows that exposure to air pollution was significantly correlated with an increased risk of becoming infected and dying due to COVID-19. Thus, these results show that the NO₂ and PM₁₀ levels in CABA can serve as one of the indicators to assess vulnerability to COVID-19. In addition, decision-makers can use this information to adopt strategies to restrict human mobility during the COVID-19 pandemic and future outbreaks of similar diseases in CABA.