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 open-access 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.
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 methodologically 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 information 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 generally 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. CoCO2-MOSAIC 1.0 is freely available at zenodo (10.5281/zenodo.7092358; Urraca et al., 2023) and at the JRC Data Catalogue (https://data.jrc.ec.europa.eu/dataset/6c8f9148-ce09-4dca-a4d5-422fb3682389, last access: 15 May 2023; Urraca Valle et al., 2023).
The changing composition of the atmosphere, driven by anthropogenic emissions, is the cause of anthropogenic climate change as well as deteriorating air quality. Emission inventories are essential to ...understand the contribution of various human activities, model and predict the changing atmospheric composition, and design cost-effective mitigation measures. At present, national emission inventories in South America (SA) focus on Greenhouse Gases (GHG) as part of their obligation to the United Nations Framework Convention for Climate Change (UNFCC) within the framework of their national communications. Emission inventories other than GHG in SA focus mainly on growing urban areas and megacities. Therefore, studies examining air quality at national, regional or continental scales in SA depend on (down-scaled) global emission inventories. This paper examines the emission estimates of air pollutants from various global inventories for five SA countries, namely Argentina, Brazil, Chile, Colombia and Peru. A more detailed analysis is conducted for the EDGAR and ECLIPSE emission inventories, in particular comparing local city-scale inventories of a major city in each country. Although total emissions between down-scaled global inventories and local city inventories are often comparable, large discrepancies exist between the sectoral contributions. This is critical, as the mitigation of poor air quality will depend on addressing the right sources. Potential sources of discrepancies between global and local inventories include the spatial distribution proxies, difference in emission factors used and/or the use of generic statistical country data when estimating emissions. This highlights the importance of using local information when generating national emission inventories, especially for air quality modeling and development of effective mitigation measures. This study represents the first step towards an increased understanding of the strengths and weaknesses of emissions information in SA.
•Emissions from various inventories for 5 South American (SA) countries are examined.•Downscaled Global & city emissions present large discrepancies for the same domain.•Global emission inventory to derive city emission for AQ modeling is not suggested.•Increasing the understanding of strengths and weaknesses of emissions data for SA.
This commentary paper from the recently formed International Global Atmospheric Chemistry (IGAC) Southern Hemisphere Working Group outlines key issues in atmospheric composition research that ...particularly impact the Southern Hemisphere. In this article, we present a broad overview of many of the challenges for understanding atmospheric chemistry in the Southern Hemisphere, before focusing in on the most significant factors that differentiate it from the Northern Hemisphere. We present sections on the importance of biogenic emissions and fires in the Southern Hemisphere, showing that these emissions often dominate over anthropogenic emissions in many regions. We then describe how these and other factors influence air quality in different parts of the Southern Hemisphere. Finally, we describe the key role of the Southern Ocean in influencing atmospheric chemistry and conclude with a description of the aims and scope of the newly formed IGAC Southern Hemisphere Working Group.
Risks associated with dust hazards are often underappreciated, a gap between the knowledge pool and public awareness that can be costly for impacted communities. This study reviews the emission ...sources and chemical, physical, and biological characteristics of airborne soil particles (dust) and their effects on human and environmental health and safety in the Pan-American region. American dust originates from both local sources (western United States, northern Mexico, Peru, Bolivia, Chile, and Argentina) and long-range transport from Africa and Asia. Dust properties, as well as the trends and interactions with criteria air pollutants, are summarized. Human exposure to dust is associated with adverse health effects, including asthma, allergies, fungal infections, and premature death. In the Americas, a well-documented and striking effect of soil dust is its association with Coccidioidomycosis, commonly known as Valley fever, an infection caused by inhalation of soil-dwelling fungi unique to this region. Besides human health, dust affects environmental health through nutrients that increase phytoplankton biomass, contaminants that diminish water supply and affect food (crops/fruits/vegetables and ready-to-eat meat), spread crop and marine pathogens, cause Valley fever among domestic and wild animals, transport heavy metals, radionuclides and microplastics, and reduce solar and wind power generation. Dust is also a safety hazard to road transportation and aviation, in the southwestern US where blowing dust is one of the deadliest weather hazards. To mitigate the harmful effects, coordinated regional and international efforts are needed to enhance dust observations and prediction capabilities, soil conservation measures, and Valley fever and other disease surveillance.
We analyze simulated sea ice changes in eight different Earth System Models that have conducted experiment G1 of the Geoengineering Model Intercomparison Project (GeoMIP). The simulated response of ...balancing abrupt quadrupling of CO2 (abrupt4xCO2) with reduced shortwave radiation successfully moderates annually averaged Arctic temperature rise to about 1°C, with modest changes in seasonal sea ice cycle compared with the preindustrial control simulations (piControl). Changes in summer and autumn sea ice extent are spatially correlated with temperature patterns but much less in winter and spring seasons. However, there are changes of ±20% in sea ice concentration in all seasons, and these will induce changes in atmospheric circulation patterns. In summer and autumn, the models consistently simulate less sea ice relative to preindustrial simulations in the Beaufort, Chukchi, East Siberian, and Laptev Seas, and some models show increased sea ice in the Barents/Kara Seas region. Sea ice extent increases in the Greenland Sea, particularly in winter and spring and is to some extent associated with changed sea ice drift. Decreased sea ice cover in winter and spring in the Barents Sea is associated with increased cyclonic activity entering this area under G1. In comparison, the abrupt4xCO2 experiment shows almost total sea ice loss in September and strong correlation with regional temperatures in all seasons consistent with open ocean conditions. The tropospheric circulation displays a Pacific North America pattern‐like anomaly with negative phase in G1‐piControl and positive phase under abrupt4xCO2‐piControl.
Key Points
Analysis of eight ESM focused on Arctic sea ice and feedback
Response of Arctic to G1 geoengineering shows clear regional differences
Sea ice is far different in detail under G1 than in pre industrial
This study delves into the photochemical atmospheric changes reported globally during the pandemic by analyzing the change in emissions from mobile sources and the contribution of local meteorology ...to ozone (O3) and particle formation in Bogotá (Colombia), Santiago (Chile), and São Paulo (Brazil). The impact of mobility reductions (50%–80%) produced by the early coronavirus-imposed lockdown was assessed through high-resolution vehicular emission inventories, surface measurements, aerosol optical depth and size, and satellite observations of tropospheric nitrogen dioxide (NO2) columns. A generalized additive model (GAM) technique was also used to separate the local meteorology and urban patterns from other drivers relevant for O3 and NO2 formation. Volatile organic compounds, nitrogen oxides (NOx), and fine particulate matter (PM2.5) decreased significantly due to motorized trip reductions. In situ nitrogen oxide median surface mixing ratios declined by 70%, 67%, and 67% in Bogotá, Santiago, and São Paulo, respectively. NO2 column medians from satellite observations decreased by 40%, 35%, and 47%, respectively, which was consistent with the changes in mobility and surface mixing ratio reductions of 34%, 25%, and 34%. However, the ambient NO2 to NOx ratio increased, denoting a shift of the O3 formation regime that led to a 51%, 36%, and 30% increase in the median O3 surface mixing ratios in the 3 respective cities. O3 showed high sensitivity to slight temperature changes during the pandemic lockdown period analyzed. However, the GAM results indicate that O3 increases were mainly caused by emission changes. The lockdown led to an increase in the median of the maximum daily 8-h average O3 of between 56% and 90% in these cities.
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