Francisco Barraza

Chemical speciation and source apportionment of fine particulate matter in Santiago, Chile, 2013

Santiago is one of the largest cities in South America and has experienced high fine particulate matter (PM2.5) concentrations in fall and winter months for decades. To better understand the sources of fall and wintertime pollution in Santiago, PM2.5 samples were collected for 24 h every weekday from March to October 2013 for chemical analysis. Samples were analyzed for mass, elemental carbon (EC), organic carbon (OC), water soluble organic carbon (WSOC), water soluble nitrogen (WSTN), secondary inorganic ions, and particle-phase organic tracers for source apportionment. Selected samples were analyzed as monthly composites for organic tracers. PM2.5 concentrations were considerably higher in the coldest months (June-July), averaging (mean ± standard deviation) 62±15 μg/m(3) in these two months. Average fine particle mass concentration during the study period was 40±20 μg/m(3). Organic matter during the peak winter months was the major component of fine particles comprising around 70% of the particle mass. Source contributions to OC were calculated using organic molecular markers and a chemical mass balance (CMB) receptor model. The four combustion sources identified were wood smoke, diesel engine emission, gasoline vehicles, and natural gas. Wood smoke was the predominant source of OC, accounting for 58±42% of OC in fall and winter. Wood smoke and nitrate were the major contributors to PM2.5. In fall and winter, wood smoke accounted for 9.8±7.1 μg/m(3) (21±15%) and nitrate accounted for 9.1±4.8 μg/m(3) (20±10%) of fine PM. The sum of secondary inorganic ions (sulfate, nitrate, and ammonium) represented about 30% of PM2.5 mass. Secondary organic aerosols contributed only in warm months, accounting for about 30% of fine PM during this time.

Source apportionment of ambient PM2.5 in Santiago, Chile: 1999 and 2004 results.

A receptor model analysis has been applied to ambient PM(2.5) measurements taken at Santiago, Chile (33.5°S, 70.7°W) in 2004 (117 samples) and in 1999 (95 samples) on a receptor site on the eastern side of the city. For both campaigns, six sources have been identified at Santiago and their contributions in 1999/2004 are: motor vehicles: 28 ± 2.5/31.2 ± 3.4%, wood burning: 24.8 ± 2.3/28.9 ± 3.3%, sulfates: 18.8 ± 1.7/16.2 ± 2.5%, marine aerosol: 13 ± 2.1/9.9 ± 1.5%, copper smelters: 11.5 ± 1.4/9.7 ± 3.3% and soil dust: 3.9 ± 1.5/4.0 ± 2.4%. Hence relative contributions are statistically the same but the absolute contributions have been reduced because ambient PM(2.5) has decreased from 34.2 to 25.1 μg/m(3) between 1999 and 2004 at Santiago. Similarity of results for both data sets - analyzed with different techniques at different laboratory facilities - shows that the analysis performed here is robust. Source identification was carried out by inspection of key species in source profiles, seasonality of source contributions, comparison with published source profiles and by looking at wind trajectories computed using the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) from USAs National Oceanic and Atmospheric Administration (NOAA); for the wood burning sources the MODIS burned area daily product was used to confirm wildfire events along the year. Using this combined methodology we have shown conclusively that: a) marine air masses do reach Santiagos basin in significant amounts but combined with anthropogenic sources; b) all copper smelters surrounding Santiago - and perhaps coal-fired power plants as well - contribute to ambient PM(2.5); c) wood burning is the second largest source, coming from residential wood burning in fall and winter and from regional wildfires in spring and summer. The results of the present analysis can be used to improve emission inventories, air quality forecasting systems and cost-benefit analyses at local and regional scales.

Source apportionment of PM10 and PM2.5 in a desert region in northern Chile

Estimating contributions of anthropogenic sources to ambient particulate matter (PM) in desert regions is a challenging issue because wind erosion contributions are ubiquitous, significant and difficult to quantify by using source-oriented, dispersion models. A receptor modeling analysis has been applied to ambient PM(10) and PM(2.5) measured in an industrial zone ~20 km SE of Antofagasta (23.63°S, 70.39°W), a midsize coastal city in northern Chile; the monitoring site is within a desert region that extends from northern Chile to southern Perú. Integrated 24-hour ambient samples of PM(10) and PM(2.5) were taken with Harvard Impactors; samples were analyzed by X Ray Fluorescence, ionic chromatography (NO(3)(-) and SO(4)(=)), atomic absorption (Na(+), K(+)) and thermal optical transmission for elemental and organic carbon determination. Receptor modeling was carried out using Positive Matrix Factorization (US EPA Version 3.0); sources were identified by looking at specific tracers, tracer ratios, local winds and wind trajectories computed from NOAAs HYSPLIT model. For the PM(2.5) fraction, six contributions were found - cement plant, 33.7 ± 1.3%; soil dust, 22.4 ± 1.6%; sulfates, 17.8 ± 1.7%; mineral stockpiles and brine plant, 12.4 ± 1.2%; Antofagasta, 8.5 ± 1.3% and copper smelter, 5.3 ± 0.8%. For the PM(10) fraction five sources were identified - cement plant, 38.2 ± 1.5%; soil dust, 31.2 ± 2.3%; mineral stockpiles and brine plant, 12.7 ± 1.7%; copper smelter, 11.5 ± 1.6% and marine aerosol, 6.5 ± 2.4%. Therefore local sources contribute to ambient PM concentrations more than distant sources (Antofagasta, marine aerosol) do. Soil dust is enriched with deposition of marine aerosol and calcium, sulfates and heavy metals from surrounding industrial activities. The mean contribution of suspended soil dust to PM(10) is 50 μg/m(3) and the peak daily value is 104 μg/m(3). For the PM(2.5) fraction, suspended soil dust contributes with an average of 9.3 μg/m(3) and a peak daily value of 31.5 μg/m(3).

Short-term dynamics of indoor and outdoor endotoxin exposure: Case of Santiago, Chile, 2012

Indoor and outdoor endotoxin in PM2.5 was measured for the very first time in Santiago, Chile, in spring 2012. Average endotoxin concentrations were 0.099 and 0.094 [EU/m(3)] for indoor (N=44) and outdoor (N=41) samples, respectively; the indoor-outdoor correlation (log-transformed concentrations) was low: R=-0.06, 95% CI: (-0.35 to 0.24), likely owing to outdoor spatial variability. A linear regression model explained 68% of variability in outdoor endotoxins, using as predictors elemental carbon (a proxy of traffic emissions), chlorine (a tracer of marine air masses reaching the city) and relative humidity (a modulator of surface emissions of dust, vegetation and garbage debris). In this study, for the first time a potential source contribution function (PSCF) was applied to outdoor endotoxin measurements. Wind trajectory analysis identified upwind agricultural sources as contributors to the short-term, outdoor endotoxin variability. Our results confirm an association between combustion particles from traffic and outdoor endotoxin concentrations. For indoor endotoxins, a predictive model was developed but it only explained 44% of endotoxin variability; the significant predictors were tracers of indoor PM2.5 dust (Si, Ca), number of external windows and number of hours with internal doors open. Results suggest that short-term indoor endotoxin variability may be driven by household dust/garbage production and handling. This would explain the modest predictive performance of published models that use answers to household surveys as predictors. One feasible alternative is to increase the sampling period so that household features would arise as significant predictors of long-term airborne endotoxin levels.

Indoor PM 2.5 in an urban zone with heavy wood smoke pollution: The case of Temuco, Chile

Temuco is a mid-size city representative of severe wood smoke pollution in southern Chile; however, little is known about the indoor air quality in this region. A field measurement campaign at 63 households in the Temuco urban area was conducted in winter 2014 and is reported here. In this study, indoor and outdoor (24-hr) PM2.5 and its elemental composition were measured and compared. Infiltration parameters and outdoor/indoor contributions to indoor PM2.5 were also determined. A statistical evaluation of how various air quality interventions and household features influence indoor PM2.5 was also performed. This study determined median indoor and outdoor PM2.5 concentrations of 44.4 and 41.8 μg/m3, respectively. An average infiltration factor (0.62 ± 0.06) was estimated using sulfur as a tracer species. Using a simple mass balance approach, median indoor and outdoor contributions to indoor PM2.5 concentrations were then estimated as 12.5 and 26.5 μg/m3, respectively; therefore, 68% of indoor PM2.5 comes from outdoor infiltration. This high percentage is due to high outdoor pollution and relatively high household air exchange rates (median: 1.06 h-1). This study found that S, Br and Rb were dominated by outdoor contributions, while Si, Ca, Ti, Fe and As originated from indoor sources. Using continuous indoor and outdoor PM2.5 measurements, a median indoor source strength of 75 μg PM2.5/min was estimated for the diurnal period, similar to literature results. For the evening period, the median estimate rose to 135 μg PM2.5/min, reflecting a more intense wood burning associated to cooking and space heating at night. Statistical test results (at the 90% confidence level) support the ongoing woodstove replacement program (reducing emissions) and household weatherization subsidies (reducing heating demand) for improving indoor air quality in southern Chile, and suggest that a cookstove improvement program might be helpful as well.