Browsing by Author "Puliafito, Enrique"

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    Civil aviation emissions in Argentina (resumen)
    (2023-06-01) Puliafito, Enrique
    The impact of aviation on climate change is reflected in increasing emissions of CO2 and other pollutants from fuel burning emitted at high altitudes, representing 2.9 % of total Greenhouse gases (GHG) emissions in 2019. However, mitigations options for decarbonization of aviation are difficult to implement given operational safety, technology maturity, energy density and other constraints. One alternative for mitigation is the use of certified sustainable aviation fuel(SAF) with lower carbon intensity than conventional jet fuel (CJF). This research presents an inventory of Argentine civil aviation emissions for its domestic and international flights, and analyzes the possibility of supplying SAF as a mitigation strategy given its abundant biomass production. Argentine aviation activity is presented as a monthly 4D (latitude, longitude, altitude and time) spatial inventory for the interval 2001–2021, based on origin and destination city pairs, aircraft types and airlines. Fuel consumption and pollutant emissions were calculated for landing-and-takeoff and cruise phases. Monthly domestic ranged from 67 to 179 kt CO2eq (2001–2019). Annual peak values occurred in 2019 consuming 560 kt CJF and direct emitting of 1.77 Mt CO2eq. While Revenue-Passenger-Kilometer (RPK) grew almost 4 times (4.18 × 109 in 2001 to 16.42 × 109 in 2019), the number of flights changed only 1.5 times (from 98,000 in 2002 to 152,000 in 2019). The main efficiency indexes varied from 97 t CJF/RPK, 308 gCO2eq/RPK to 34 t CJF/ RPK, 107 gCO2eq/RPK between 2001 and 2019, respectively, showing an average annual improvement of 3.5 % due to partial fleet renewal, especially from 2015 onwards. Emissions of other pollutants for 2019 reached total values of CO 14.14 kt; NOX 6.77 kt; PM tot 55.12 kt. For the period 2001–2019, international aviation consumed between 1 Mt - 1.5 Mt CJF, directly emitting between 3.30 and 4.80 Mt of CO2eq; RPKs went from 6.234 × 109 to 20.524 × 109; the efficiency indices ranged from 529 to 240 gCO2eq/RPK. The most important changes occurred with an optimization of routes and number of flights and the replacement of the four-engines (B747, A380) by more efficient twin-engines (B777, A330) aircraft. Argentina is not required to any offsetting regulatory program due to its small aviation market (approX. 0.22 % global market in 2019), nor has to date certified SAF production pathways, nevertheless it has potential for SAF availability based on actual biofuels production (ethanol, biodiesel and soybean oil) and biomass feedstock's existences. In this sense this studies proposes that 2019 domestic fuel consumption could be supplied using 79 % exportable amounts of sugarcane ethanol (257 ± 53 kt) (by Ethanol to Jet ETJ) and 34 % of exportable soybean oil (1079 ± 160 kt) (by hydroprocessed esters and fatty acids- HEFA) pathways. For this scenario average GHG emissions reached 1.321 ± 0.115 Mt CO2eq; which would imply a 62 % of the current emission value using CJF (2.17Mt CO2eq), or savings of about 838 kt CO2eq (38 %). At the 2019 level of harvest and biofuel production, up to 1.4 Mt of SAF could be produced from sugarcane ethanol/ETJ and soybean oil/HEFA mitigating up to 1.8 MtCO2eq. A 35 kt CO2eq annual sectoral national mitigation strategy could be reached by using 14 kt of SAF.
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    CoCO2-MOSAIC 1.0: a global mosaic of regional, gridded, fossil, and biofuel CO2 emission inventories (resumen)
    (2024-06-22) Berna Peña, Lucas; Lopez Noreña, Ana; Puliafito, Enrique
    Gridded bottom-up inventories of CO2 emissions are needed in global CO2 inversion schemes as priors to initialize transport models and as a complement to top-down estimates to identify the anthropogenic sources. Global inversions require gridded datasets almost in near-real time that are spatially and methodologi- cally consistent at a global scale. This may result in a loss of more detailed information that can be assessed by using regional inventories because they are built with a greater level of detail including country-specific infor- mation and finer resolution data. With this aim, a global mosaic of regional, gridded CO2 emission inventories, hereafter referred to as CoCO2-MOSAIC 1.0, has been built in the framework of the CoCO2 project. CoCO2-MOSAIC 1.0 provides gridded (0.1 ◦ 0.1 × ◦ ) monthly emissions fluxes of CO2 fossil fuel (CO2ff, long cycle) and CO2 biofuel (CO2bf, short cycle) for the years 2015–2018 disaggregated in seven sectors. The regional inventories integrated are CAMS-REG-GHG 5.1 (Europe), DACCIWA 2.0 (Africa), GEAA-AEI 3.0 (Argentina), INEMA 1.0 (Chile), REAS 3.2.1 (East, Southeast, and South Asia), and VULCAN 3.0 (USA). EDGAR 6.0, CAMS-GLOB-SHIP 3.1 and CAMS-GLOB-TEMPO 3.1 are used for gap-filling. CoCO2-MOSAIC 1.0 can be recommended as a global baseline emission inventory for 2015 which is regionally accepted as a reference, and as such we use the mosaic to inter-compare the most widely used global emission inventories: CAMS-GLOB- ANT 5.3, EDGAR 6.0, ODIAC v2020b, and CEDS v2020_04_24. CoCO2-MOSAIC 1.0 has the highest CO2ff (36.7 Gt) and CO2bf (5.9 Gt) emissions globally, particularly in the USA and Africa. Regional emissions gener- ally have a higher seasonality representing better the local monthly profiles and are generally distributed over a higher number of pixels, due to the more detailed information available. All super-emitting pixels from regional inventories contain a power station (CoCO2 database), whereas several super-emitters from global inventories are likely incorrectly geolocated, which is likely because regional inventories provide large energy emitters as point sources including regional information on power plant locations.
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    Contaminación atmosférica e hídrica en Argentina - Contribuciones del V Congreso PROIMCA y III Congreso PRODECA - 2015
    (edUTecNe, 2015-08-01) Puliafito, Enrique; Allende, David; Panigatti, Cecilia; Ruggeri, María Florencia
    Selección de artículos completos y resúmenes del Quinto Congreso del Proyecto Integrador para la Mitigación de la Contaminación Atmosférica (PROIMCA) y Tercer Congreso del Proyecto Integrador para la Determinación de la Calidad del Agua (PRODECA)
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    High-resolution seasonal and decadal inventory of anthropogenic gas-phase and particle emissions for Argentina (resumen)
    (2021-10-01) Puliafito, Enrique; Bolaño Ortíz, Tomás; Berna, Lucas; Pascual Flores, Romina; Urquiza, Josefina; Lopez Noreña, Ana; Tames, María
    This work presents the integration of a gas-phase and particulate atmospheric emission inventory (AEI) for Argentina in high spatial resolution (; 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, NOx (NO+NO2), and non-methane volatile organic compounds (NMVOCs); (iii) acidifying gases – NH3 and SO2; and (iv) particulate matter (PM) – PM10, PM2.5, 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.
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    Influence of emission inventory resolution on the modeled spatio-temporal distribution of air pollutants in Buenos Aires, Argentina, using WRF-Chem (resumen)
    (2021-11-01) Lopez Noreña, Ana; Berná, Lucas; Tames, Florencia; Puliafito, Enrique; Fernandez, Rafael
    The temporal and spatial resolution of the emission inventory included into an air quality model plays a key role in the appropriate representation of air pollution events and background atmospheric chemistry. Here, we use the Weather Research and Forecasting coupled with Chemistry (WRF-Chem v4.0) model to perform highresolution air quality simulations over the city of Buenos Aires, Argentina, with two different anthropogenic emissions datasets: the High-resolution Emissions Inventory of Argentina (GEAA-AEI) and the Emissions Database for Global Atmospheric Research - Hemispheric Transport of Air Pollution (EDGAR-HTAP). A local optimized configuration considering 3 nested domains with a horizontal grid size of 20 × 20 km, 4 × 4 km, and 1.3 × 1.3 km and the MOZART chemical scheme was used. The model performance for NO2, PM10, PM2.5, and O3 concentrations was validated against measurements from the existing air quality monitoring stations in the Buenos Aires Metropolitan Area (AMBA) during austral fall 2018. Our results show that the daytime concentrations of air pollutants are influenced by the shape and shift of the hourly emissions profile, especially for NO2 where the reduction in nighttime emissions decreased the mean model bias by ~50%. PM10 and PM2.5 generally satisfied the model performance criteria, but underestimation tended to occur in the GEAA-AEI simulations and overestimation for the EDGAR-HTAP case. Comparison with TROPOMI-derived tropospheric NO2 columns showed a high positive correlation (r > 0.75) and a positive bias. We found large discrepancies between the spatial distribution patterns of the simulations within the innermost high-resolution domain centered on AMBA, mostly in suburban areas where no observations are available. We propose additional monitoring sites to address such differences and determine the size and shape of the main pollutant plume. We conclude that high-resolution air quality modeling is important within underdeveloped or developing South American cities that lack continuous air quality measurements, as it represents a powerful tool in supporting the design of governmental monitoring networks and air pollution mitigation policies.
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    Influencia de la dinámica poblacional sobre las emisiones de carbono. Análisis de indicadores tecnológicos
    (2011-04-01) Castesana, Paula; Puliafito, Enrique
    Actualmente, el análisis de las transiciones demográficas sobre el crecimiento económico ha cobrado relevancia en el debate sobre el cambio climático. El impacto de dichas transiciones influye directamente sobre el consumo de bienes y energía primaria y sobre las emisiones de carbono, modificando la acumulación de gases de efecto invernadero en la atmósfera. Este trabajo propone analizar las tendencias globales y regionales de los distintos factores relacionados con las emisiones antrópicas de carbono. El estudio de los resultados permitirá proponer diversas medidas para producir una estabilización o reducción efectiva de las emisiones antrópicas de CO2
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    Inventario de emisiones atmosféricas del sector energético argentino
    (2018-04-01) Puliafito, Enrique; Castesana, Paula; Allende, David; Ruggeri, Florencia; Pinto, Sebastián; Pascual, Romina
    Se presentan los detalles metodológicos para la preparación de un inventario de alta resolución (2,5 km × 2,5 km), de las principales emisiones a la atmósfera provenientes de las actividades energéticas de Argentina. Los subsectores considerados son: generación pública de energía eléctrica, refinerías de petróleo, producción de cemento, transporte (marítimo, aéreo, ferroviario y caminero), residencial y comercial. Los contaminantes considerados incluyen gases de efecto invernadero y precursores de ozono: CO2, CH4, NOx, N2O, VOC; y otros indicadores específicos de calidad del aire como PM10, PM2.5, SOx, Pb, POPs entre otros. Se describe la desagregación espacial utilizada para estimar las emisiones de provenientes de fuentes de naturaleza diversas como residenciales, vehiculares, o industriales, a fin de tener un mapa grillado único que pueda usarse en modelos regionales de calidad del aire que mejore o complete las bases de datos existentes. Se aprecia que el 18% de las emisiones residenciales se generan en las zonas rurales (< 2 500 hab/km2), 44% se generan en las zonas urbanas de densidad media (>= 2 500 < 7 500 hab/km2), el 38% restante se emiten en ciudades medias y densamente pobladas (> 7 500 hab/km2). Para las fuentes puntuales se observa que el 43% de las emisiones de dióxido de carbono (22 500 Gg) se emiten en la zona Pampeana (Buenos Aires, CABA y La Pampa) seguido del 24% (de la zona Centro (12 100 Gg), Córdoba, Santa Fe, Entre Ríos y Santiago del Estero); el resto del país emite el (32%: 16 350 Gg). En el transporte la zona pampeana y central concentra el 60% de la actividad y las emisiones. En definitiva, se aprecia una importante disparidad geográfica de las emisiones dependiendo del tipo de fuentes. Sin embargo, las zonas urbanas concentran más del 75% de las emisiones en un territorio menor al 3%.
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    Optimización del transporte público en la ciudad de Mendoza y consideraciones ambientales
    (2016-10-01) Zanitti, Ayelén; Puliafito, Enrique
    El transporte público en la ciudad de Mendoza está compuesto por trolebuses, trenes, autobu- ses y minibúses. El 30% de su población utiliza el sistema de transporte público regularmen- te, y el resto utiliza el coche para sus traslados diarios, cuando el promedio de ocupantes que viajan en los vehículos propios es de 1,4 pasajeros. Ambos factores conllevan a que la ciudad esté cada vez más congestionada y contaminada. El objetivo de este artículo es la búsqueda de una metodología que permita lograr la optimización y distribución eficaz de los vehículos que conforman el transporte público en la ciudad de Mendoza, que minimice el consumo de combustible, y produzca la menor emisión, a partir de un parque automotor y recorridos dados. La continuación de esta investigación está orientada a desarrollar un modelo que permita lograr una mejora significativa en el sistema de transporte público y en la calidad del aire en esa ciudad.
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    PAPILA dataset : a regional emission inventory of reactive gases for South America based on the combination of local and global information (resumen)
    (2022-06-01) Puliafito, Enrique
    The multidisciplinary project Prediction of Air Pollution in Latin America and the Caribbean (PAPILA) is dedicated to the development and implementation of an air quality analysis and forecasting system to assess pollution impacts on human health and economy. In this context, a comprehensive emission inventory for South America was developed on the basis of the existing data on the global dataset CAMS-GLOB-ANT v4.1 (developed by joining CEDS trends and EDGAR v4.3.2 historical data), enriching it with data derived from locally available emission inventories for Argentina, Chile, and Colombia. This work presents the results of the first joint effort of South American researchers and European colleagues to generate regional maps of emissions, together with a methodological approach to continue incorporating information into future versions of the dataset. This version of the PAPILA dataset includes CO, NOx, NMVOCs, NH3, and SO2 annual emissions from anthropogenic sources for the period 2014–2016, with a spatial resolution of 0.1◦ 0.1◦ over a domain that covers 32–120◦ W and 34◦ N–58◦ S. The PAPILA dataset is presented as netCDF4 files and is available in an openaccess data repository under a CC-BY 4 license: https://doi.org/10.17632/btf2mz4fhf.3 (Castesana et al., 2021). A comparative assessment of PAPILA–CAMS datasets was carried out for (i) the South American region, (ii) the countries with local data (Argentina, Colombia, and Chile), and (iii) downscaled emission maps for urban domains with different environmental and anthropogenic factors. Relevant differences were found at both country and urban levels for all the compounds analyzed. Among them, we found that when comparing PAPILA total emissions versus CAMS datasets at the national level, higher levels of NOx and considerably lower levels of the other species were obtained for Argentina, higher levels of SO2 and lower levels of CO and NOx for Colombia, and considerably higher levels of CO, NMVOCs, and SO2 for Chile. These discrepancies are mainly related to the representativeness of local practices in the local emission estimates, to the improvements made in the spatial distribution of the locally estimated emissions, or to both. Both datasets were evaluated against surface concentrations of CO and NOx by using them as input data to the WRF-Chem model for one of the analyzed domains, the metropolitan area of Buenos Aires, for summer and winter of 2015. PAPILA-based modeling results had a smaller bias for CO and NOx concentrations in winter while CAMS-based results for the same period tended to deliver an underestimation of these concentrations. Both inventories exhibited similar performances for CO in summer, while the PAPILA simulation outperformed CAMS for NOx concentrations. These results highlight the importance of refining global inventories with local data to obtain accurate results with high-resolution air quality models.
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    Spread COVID-19 during Godzilla African dust in June 2020 on the Colombian Caribbean region (resumen)
    (2023-07-16) Puliafito, Enrique
    Recent studies show that aerosols are highly linked to the spread of the COVID—19 pandemic. Furthermore, during this pandemic, the largest Saharan dust intrusion event has reached the Caribbean region in the last 20 years, called “Godzilla” African Dust or GAD. This study aims to analyze the correlation between the spread of COVID—19 and the GAD event in the main cities of the Colombian Caribbean region. The results showed a positive correlation between the spread of COVID—19 and the GAD event in most cities. Our findings could serve as input for the development of a strategy in the prevention of COVID—19 and other similar viral diseases during the Saharan dust intrusion events that reach the Caribbean region each year from Africa. Our results may help design strategies to prevent future outbreaks of COVID-19 and reduce the risk of future pandemics of similar viral diseases. Especially during the Saharan dust intrusion events that reach the Caribbean region each year
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    The impact on air quality of PM10 emissions from the bus fleet of Buenos Aires City (resumen)
    (2022-11-21) Puliafito, Enrique; Accorinti, Jesica; Allende, David
    Automobile transport in megacities poses serious problems in the area of sustainability and environmental security. In the City of Buenos Aires (CABA) it represents 37% of GHG emissions and is an important source of pollutants dangerous to human health. As such, it is an energy consumption sector targeted for the implementation of methods that allow for sustainable urban transport. At the same time, very few previous studies about transport vehicle emissions have utilized the PM10 as an indicator of environmental contamination, considering that the negative impact of this environmental contaminant on human health is widely studied. An emission model linked to an atmospheric dispersion model, statistically validated, were used to study different scenarios of emissions generated by diesel buses. It was observed that in a scenario of zero bus emissions (E0), PM10 immission (air concentrations) concentration in CABA is reduced by half. When studying the energy transition from diesel buses to electric energy, while the rest of the vehicle fleet was maintained at the expense of fossil fuels, the local immission concentration of PM10 in CABA was of the same magnitude of that which was obtained when simulating the (E0) scenario of only private vehicle fleet. This study is relevant in the evaluation of public policy on vehicle emission mitigation that seeks to reduce health risks from poor air quality and to develop a more progressively sustainable city.
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    Tracking unaccounted greenhouse gas emissions due to the war in Ukraine since 2022 (resumen)
    (2024-03-01) Puliafito, Enrique
    Accounting and reporting of greenhouse gas (GHG) emissions are mandatory for Parties under the Paris Agreement. Emissions reporting is important for understanding the global carbon cycle and for addressing global climate change. However, in a period of open conflict or war, military emissions increase significantly and the accounting system is not currently designed to account adequately for this source. In this paper we analyze how, during the first 18 months of the 2022/2023 full-scale war in Ukraine, GHG national inventory reporting to the UNFCCC was affected. We estimated the decrease of emissions due to a reduction in traditional human activities. We identified major, war-related, emission processes from the territory of Ukraine not covered by current GHG inventory guidelines and that are not likely to be included in national inventory reports. If these emissions are included, they will likely be incorporated in a way that is not transparent with potentially high uncertainty. We analyze publicly available data and use expert judgment to estimate such emissions from (1) the use of bombs, missiles, barrel artillery, and mines; (2) the consumption of oil products for military operations; (3) fires at petroleum storage depots and refineries; (4) fires in buildings and infrastructure facilities; (5) fires on forest and agricultural lands; and (6) the decomposition of war-related garbage/waste. Our estimate of these war-related emissions of carbon dioXide, methane, and nitrous oXide for the first 18 months of the war in Ukraine is 77 MtCO2-eq. with a relative uncertainty of +/—22 % (95 % confidence interval).