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Quantifying source contributions to indoor PM 2.5 levels by indoor PM 2.5 sources has been limited by the costs associated with chemical speciation analyses of indoor PM 2.5 samples. Here, we propose a new methodology to estimate this contribution. We applied FUzzy SpatioTemporal Apportionment (FUSTA) to a database of indoor and outdoor PM 2.5 concentrations in school classrooms plus surface meteorological data to determine the main spatiotemporal patterns (STPs) of PM 2.5 . We found four dominant STPs in outdoor PM 2.5 , and we denoted them as regional, overnight mix, traffic, and secondary PM 2.5 . For indoor PM 2.5, we found the same four outdoor STPs plus another STP with a distinctive temporal evolution characteristic of indoor-generated PM 2.5 . Concentration peaks were evident for this indoor STP due to children's activities and classroom housekeeping, and there were minimum contributions on sundays when schools were closed. The average indoor-generated estimated contribution to PM 2.5 was 5.7 μg m -3 , which contributed to 17% of the total PM 2.5 , and if we consider only school hours, the respective figures are 8.1 μg m -3 and 22%. A cluster-wise indoor-outdoor PM 2.5 regression was applied to estimate STP-specific infiltration factors ( F inf ) per school. The median and interquartile range (IQR) values for F inf are 0.83 [0.7-0.89], 0.76 [0.68-0.84], 0.72 [0.64-0.81], and 0.7 [0.62-0.9], for overnight mix, secondary, traffic, and regional sources, respectively. This cost-effective methodology can identify the indoor-generated contributions to indoor PM 2.5 , including their temporal variability.

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) PM 2.5 and its elemental composition were measured and compared. Infiltration parameters and outdoor/indoor contributions to indoor PM 2.5 were also determined. A statistical evaluation of how various air quality interventions and household features influence indoor PM 2.5 was also performed. This study determined median indoor and outdoor PM 2.5 concentrations of 44.4 and 41.8 μg/m 3 , 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 PM 2.5 concentrations were then estimated as 12.5 and 26.5 μg/m 3 , respectively; therefore, 68% of indoor PM 2.5 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 PM 2.5 measurements, a median indoor source strength of 75 μg PM 2.5 /min was estimated for the diurnal period, similar to literature results. For the evening period, the median estimate rose to 135 μg PM 2.5 /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., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

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., (Copyright © 2016 Elsevier Ltd. All rights reserved.)