Browsing by Author "Villalobos, Ana María"

Now showing 1 - 6 of 6
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    A new methodology for source apportionment of gaseous industrial emissions
    (2023) Jorquera, Héctor; Villalobos, Ana María; CEDEUS (Chile)
    Air quality modeling (AQM) is often used to investigate gaseous pollution around industrial zones. However, this methodology requires accurate emission inventories, unbiased AQM algorithms and realistic boundary conditions. We introduce a new methodology for source apportionment of industrial gaseous emissions, which is based on a fuzzy clustering of ambient concentrations, along with a standard AQM approach. First, by applying fuzzy clustering, ambient concentration is expressed as a sum of non-negative contributions — each corresponding to a specific spatiotemporal pattern (STP); we denote this method as FUSTA (FUzzy SpatioTemporal Apportionment). Second, AQM of the major industrial emissions in the study zone generates another set of STP. By comparing both STP sets, all major source contributions resolved by FUSTA are identified, so a source apportionment is achieved. The uncertainty in FUSTA results may be estimated by comparing results for different numbers of clusters. We have applied FUSTA in an industrial zone in central Chile, obtaining the contributions from major sources of ambient SO2: a thermal power plant complex and a copper smelter, and other contributions from local and regional sources (outside the AQM domain). The methodology also identifies SO2 episodes associated to emissions from the copper smelter.
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    Combining Cluster Analysis of Air Pollution and Meteorological Data with Receptor Model Results for Ambient PM2.5 and PM10
    (2020) Jorquera, Héctor; Villalobos, Ana María; CEDEUS (Chile)
    Air pollution regulation requires knowing major sources on any given zone, setting specific controls, and assessing how health risks evolve in response to those controls. Receptor models (RM) can identify major sources: transport, industry, residential, etc. However, RM results are typically available for short term periods, and there is a paucity of RM results for developing countries. We propose to combine a cluster analysis (CA) of air pollution and meteorological measurements with a short-term RM analysis to estimate a long-term, hourly source apportionment of ambient PM2.5 and PM10. We have developed a proof of the concept for this proposed methodology in three case studies: a large metropolitan zone, a city with dominant residential wood burning (RWB) emissions, and a city in the middle of a desert region. We have found it feasible to identify the major sources in the CA results and obtain hourly time series of their contributions, effectively extending short-term RM results to the whole ambient monitoring period. This methodology adds value to existing ambient data. The hourly time series results would allow researchers to apportion health benefits associated with specific air pollution regulations, estimate source-specific trends, improve emission inventories, and conduct environmental justice studies, among several potential applications.
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    Local and NON-LOCAL source apportionment of black carbon and combustion generated PM2.5
    (Elsevier Ltd, 2024) Rodríguez Rangel, Jessika Carolina; Villalobos, Ana María; Castro-Molinare J.; Jorquera González, Héctor Iván Joaquin; CEDEUS (Chile)
    Current methods for measuring black carbon aerosol (BC) by optical methods apportion BC to fossil fuel and wood combustion. However, these results are aggregated: local and non-local combustion sources are lumped together. The spatial apportioning of carbonaceous aerosol sources is challenging in remote or suburban areas because non-local sources may be significant. Air quality modeling would require highly accurate emission inventories and unbiased dispersion models to quantify such apportionment. We propose FUSTA (FUzzy SpatioTemporal Apportionment) methodology for analyzing aethalometer results for equivalent black carbon coming from fossil fuel (eBCff) and wood combustion (eBCwb). We applied this methodology to ambient measurements at three suburban sites around Santiago, Chile, in the winter season 2021. FUSTA results showed that local sources contributed ∼80% to eBCff and eBCwb in all sites. By using PM2.5 – eBCff and PM2.5 – eBCwb scatterplots for each fuzzy cluster (or source) found by FUSTA, the estimated lower edge lines showed distinctive slopes in each measurement site. These slopes were larger for non-local sources (aged aerosols) than for local ones (fresh emissions) and were used to apportion combustion PM2.5 in each site. In sites Colina, Melipilla and San Jose de Maipo, fossil fuel combustion contributions to PM2.5 were 26 % (15.9 μg m−3), 22 % (9.9 μg m−3), and 22 % (7.8 μg m−3), respectively. Wood burning contributions to PM2.5 were 22 % (13.4 μg m−3), 19 % (8.9 μg m−3) and 22% (7.3 μg m−3), respectively. This methodology generates a joint source apportionment of eBC and PM2.5, which is consistent with available chemical speciation data for PM2.5 in Santiago.
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    Spatiotemporal Analysis of Black Carbon Sources: Case of Santiago, Chile, under SARS-CoV-2 Lockdowns
    (2022) Adasme, Carla; Villalobos, Ana María; Jorquera, Héctor; CEDEUS (Chile)
    Background: The SARS-CoV-2 pandemic has temporarily decreased black carbon emissions worldwide. The use of multi-wavelength aethalometers provides a quantitative apportionment of black carbon (BC) from fossil fuels (BCff) and wood-burning sources (BCwb). However, this apportionment is aggregated: local and non-local BC sources are lumped together in the aethalometer results. Methods: We propose a spatiotemporal analysis of BC results along with meteorological data, using a fuzzy clustering approach, to resolve local and non-local BC contributions. We apply this methodology to BC measurements taken at an urban site in Santiago, Chile, from March through December 2020, including lockdown periods of different intensities. Results: BCff accounts for 85% of total BC; there was up to an 80% reduction in total BC during the most restrictive lockdowns (April–June); the reduction was 40–50% in periods with less restrictive lockdowns. The new methodology can apportion BCff and BCwb into local and non-local contributions; local traffic (wood burning) sources account for 66% (86%) of BCff (BCwb). Conclusions: The intensive lockdowns brought down ambient BC across the city. The proposed fuzzy clustering methodology can resolve local and non-local contributions to BC in urban zones.
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    Temporal evolution of main ambient PM2.5 sources in Santiago, Chile, from 1998 to 2012.
    (2017) Barraza Saavedra, Francisco Javier; Lambert, Fabrice; Jorquera, Héctor; Villalobos, Ana María; Gallardo, Laura; CEDEUS (Chile)
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    Wood burning pollution in Chile: A tale of two mid-size cities
    (2021) Jorquera, Héctor; Villalobos, Ana María; Schauer, James J.; CEDEUS (Chile)
    Cities in southern Chile are facing high levels of PM2.5 because of wood burning pollution. We quantify the contribution of wood smoke to fine particles in two mid-size cities: Molina and Valdivia, located in different climate zones. The sampling campaigns were carried out during austral winter (July to September) in 2018 (Molina) and 2019 (Valdivia). 24-h filter samples were analyzed for carbonaceous compounds, secondary ions, metals, and particle-phase organic molecular markers. Average winter concentrations of PM2.5 were 53 ± 32 μg/m3 (average ± standard deviation) in Molina and 89 ± 55 μg/m3 in Valdivia. The major component of fine particles was organic matter, representing more than 70% of PM2.5. Concentrations of organic molecular markers were used in a receptor model (US EPA CMB8.2) to identify and quantify primary sources of PM2.5. The major source of PM2.5 was wood smoke, which accounted for 41.55 ± 9.77 μg/m3 (62.9 ± 15.3%) in Molina and 43.65 ± 24.06 μg/m3 (51.7 ± 21.1%) in Valdivia. Secondary organic aerosols (SOA) generated from inefficient wood burning, contributed 20.4 ± 17.7% in Molina and 28.9 ± 27.6% in Valdivia. Secondary inorganic ions and dust are minor sources of PM2.5. The total contribution of wood smoke (adding primary wood smoke and SOA) could be as much as 83% in Molina and 81% in Valdivia, during the winter season.