This work presents the integration of a gas-phase and particulate atmospheric emission inventory (AEI) for Argentina in high spatial resolution ($\mathrm{0.025}{}^{\circ }\times \mathrm{0.025}{}^{\circ }$ ; approx. 2.5 km×2.5 km) considering monthly variability from 1995 to 2020. The new inventory, called GEAA-AEIv3.0M, includes the following activities: energy production, fugitive emissions from oil and gas production, industrial fuel consumption and production, transport (road, maritime, and air), agriculture, livestock production, manufacturing, residential, commercial, and biomass and agricultural waste burning. The following species, grouped by atmospheric reactivity, are considered: (i) greenhouse gases (GHGs) – CO₂, CH₄, and N₂O; (ii) ozone precursors – CO, NO_x (NO+NO₂), and non-methane volatile organic compounds (NMVOCs); (iii) acidifying gases – NH₃ and SO₂; and (iv) particulate matter (PM) – PM₁₀, PM_2.5, total suspended particles (TSPs), and black carbon (BC). The main objective of the GEAA-AEIv3.0M high-resolution emission inventory is to provide temporally resolved emission maps to support air quality and climate modeling oriented to evaluate pollutant mitigation strategies by local governments. This is of major concern, especially in countries where air quality monitoring networks are scarce, and the development of regional and seasonal emissions inventories would result in remarkable improvements in the time and space chemical prediction achieved by air quality models. Despite distinguishing among different sectoral and activity databases as well as introducing a novel spatial distribution approach based on census radii, our high-resolution GEAA-AEIv3.0M shows equivalent national-wide total emissions compared to the Third National Communication of Argentina (TNCA), which compiles annual GHG emissions from 1990 through 2014 (agreement within ±7.5 %). However, the GEAA-AEIv3.0M includes acidifying gases and PM species not considered in TNCA. Temporal comparisons were also performed against two international databases: Community Emissions Data System (CEDS) and EDGAR HTAPv5.0 for several pollutants; for EDGAR it also includes a spatial comparison. The agreement was acceptable within less than 30 % for most of the pollutants and activities, although a >90 % discrepancy was obtained for methane from fuel production and fugitive emissions and >120 % for biomass burning. Finally, the updated seasonal series clearly showed the pollution reduction due to the COVID-19 lockdown during the first quarter of year 2020 with respect to same months in previous years. Through an open-access data repository, we present the GEAA-AEIv3.0M inventory as the largest and more detailed spatial resolution dataset for the Argentine Republic, which includes monthly gridded emissions for 12 species and 15 stors between 1995 and 2020. The datasets are available at https://doi.org/10.17632/d6xrhpmzdp.2 (Puliafito et al., 2021), under a CC-BY 4 license.

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.

The aim of this work was to analyze the changes in the emissions from the transport sector during the COVID-19 lockdown in Colombia. We compared estimated emissions from road transportation of four groups of pollutants, namely, greenhouse gases (CO₂, CH₄, N₂O), ozone precursor gases (CO, NMVOC, NOx), aerosols (BC, PM_2.5, PM₁₀), and acidifying gases (NH₃, SO₂), during the first half of 2020 with values obtained in the same period of 2018. The estimate of emissions from road transportation was determined using a standardized methodology consistent with the 2006 Intergovernmental Panel on Climate Change (IPCC) Guidelines for National Greenhouse Gas Inventories and the European Environment Agency/European Monitoring and Evaluation Program. We found a substantial reduction in GHG emissions for CH₄, N₂O, and CO₂ by 17%, 21%, and 28%, respectively. The ozone precursors CO and NMVOC presented a decrease of 21% and 22%, respectively, while NOx emissions were reduced up to 15% for the study period. In addition, BC decreased 15%, and there was a reduction of 17% for both PM₁₀ and PM_2.5 emissions. Finally, acidifying gases presented negative variations of 19% for SO₂ and 23% for NH₃ emissions. Furthermore, these results were consistent with the Ozone Monitoring Instrument (OMI) satellite observations and measurements at air quality stations. Our results suggest that the largest decreases were due to the reduction in the burning of gasoline and diesel oil from the transport sector during the COVID-19 lockdown. These results can serve decision makers in adopting strategies to improve air quality related to the analyzed sector.

This work presents an analysis of fire events recorded in Isla Salamanca Natural Park and their impact on the air quality in the district of Barranquilla, with an emphasis on 2020 due to the increase in the number of ha burned by forest fires that year. The analysis was based on the data provided by the environmental authority for 2015–2020. The average number of ha burned in 2020 was 50% (events recorded since 2015), with a total area of fires corresponding to 256.9 ha, which is of concern considering the ecological importance of the park and its proximity to the district of Barranquilla, Colombia. The study evaluated the spatial–temporal distributions of forest fires and their possible direct effects on air quality. For 2020, it was found that the maximum hourly measurements of the Tres Ave Marias station for particulate matter less than 2.5 (135.013 µg/m³) corresponded to the recorded event that occurred in June 2020, whereas those of the Móvil station for PM₁₀ (263.98 µg/m³) and PM_2.5 (278.7 µg/m³) corresponded to the events of 28 June 2020, and 9 August 2020. These concentrations were higher than the standard values of the average maximum limits for 24 h established in the current Colombian regulations, and both events coincided with fire events reported by the environmental authorities, where a total of 249 ha of Isla Salamanca Natural Park were burned. These things considered, it was evident that the Policía station had the highest concentrations of pollutants on average.

Fire is a process of disturbance of natural ecosystems that can be used for land management and soil preparation for agricultural purposes, but can also drastically affect biodiversity and the distribution and abundance of species by changing land use and altering the microclimate. The analysis of data on thermal anomalies has become a valuable tool for the study of places with low monitoring of the occurrence of fires. In this study, information from the MODIS sensor was used to analyze the spatio-temporal distribution of fires in the five natural regions of Colombia (Caribbean, Andean, Pacific, Orinoquia, and Amazon) in the period of 2000–2020. Nevertheless, MODIS fire hotspots present some difficulties in estimating the magnitude of fire activity, due the relations between active fires and burned areas, which are not constant in space and time. The method used in this work consisted to performance an inter-annual and intra-annual analysis of thermal anomalies data and identifying the incidence of temperature in the occurrence of fires. The fire density (defined as the number of fires per unit area) and the fire trends over the study period were also analyzed. Inter-annual fire peaks were recorded in 2004 (8.21%) and 2007 (8.04%), and three main fire hotspots were identified in the Orinoquia, Andean, and Caribbean regions. Moreover, 87% of fire peaks were observed in the dry season (December–March). On the other hand, the highest incidence of thermal anomalies occurred in the Orinoquia region (83409 ± 185 fires), and the highest incidence of fires per unit area was recorded in the Andean region (0.162 ± 0.086 fires-km²-year). Fire activities varied strongly according to region and year over the study period. Significant correlations were observed between temperature and fire density in the Andean (Rho = 0.7506), Pacific (Rho = 0.7364), and Caribbean (Rho = 0.5571) regions. Thus, temperature seem to be a driver of fire density in these regions.