Indoor Fine Particulate Matter Concentrations Research Articles

Using Low-Cost Sensing Technology to Assess Ambient and Indoor Fine Particulate Matter Concentrations in New York during the COVID-19 Lockdown

Air pollution is a leading cause of death in the United States and is associated with adverse health outcomes, including increased vulnerability to coronavirus disease 2019 (COVID-19). The AirBeam2 was used to measure particulate matter with a diameter of 2.5 μm or smaller (PM2.5) to investigate differences between indoor and ambient levels at seven private homes in New York during and after the COVID-19 lockdown. Measurements taken in 2020 fall, 2021 winter, and 2022 fall showed that at 90% of the sites, indoor PM2.5 levels exceeded outdoor levels both during and after the COVID-19 lockdown, p = 0.03, possibly exceeding safety levels. Higher indoor PM2.5 levels attributed to little or no ventilation in the basement and kitchens from cooking and smoke were greater in fall than in winter. Higher ambient PM2.5 levels were attributed to vehicular traffic at a street-facing sampling site. PM2.5 sources identified in this study may help in devising control strategies to improve indoor air quality (IAQ) and consequently alleviate respiratory health effects. These findings may be used as a basis for in-house modifications, including natural ventilation and the use of air purifiers to reduce exposures, mitigate future risks, and prevent potential harm to vulnerable residents.

Evaluation of random forest regression and multiple linear regression for predicting indoor fine particulate matter concentrations in a highly polluted city

BackgroundIndoor and outdoor fine particulate matter (PM2.5) are both leading risk factors for death and disease, but making indoor measurements is often infeasible for large study populations. MethodsWe developed models to predict indoor PM2.5 concentrations for pregnant women who were part of a randomized controlled trial of portable air cleaners in Ulaanbaatar, Mongolia. We used multiple linear regression (MLR) and random forest regression (RFR) to model indoor PM2.5 concentrations with 447 independent 7-day PM2.5 measurements and 87 potential predictor variables obtained from outdoor monitoring data, questionnaires, home assessments, and geographic data sets. We also developed blended models that combined the MLR and RFR approaches. All models were evaluated in a 10-fold cross-validation. ResultsThe predictors in the MLR model were season, outdoor PM2.5 concentration, the number of air cleaners deployed, and the density of gers (traditional felt-lined yurts) surrounding the apartments. MLR and RFR had similar performance in cross-validation (R2 = 50.2%, R2 = 48.9% respectively). The blended MLR model that included RFR predictions had the best performance (cross validation R2 = 81.5%). Intervention status alone explained only 6.0% of the variation in indoor PM2.5 concentrations. ConclusionsWe predicted a moderate amount of variation in indoor PM2.5 concentrations using easily obtained predictor variables and the models explained substantially more variation than intervention status alone. While RFR shows promise for modelling indoor concentrations, our results highlight the importance of out-of-sample validation when evaluating model performance. We also demonstrate the improved performance of blended MLR/RFR models in predicting indoor air pollution.

Assessment of Modeled Indoor Air Concentrations of Particulate Matter, Gaseous Pollutants, and Volatile Organic Compounds Emitted from Candles

ABSTRACT Candle burning is regarded as an important source of airborne pollutants in indoor environments. Indoor concentrations of aldehydes, benzo(a)pyrene, sulphur dioxide (SO2), nitrogen oxides (NOx), and particulate matter (PM) produced from the burning of scented candles and raw materials with different melting point/oil content (50/1, 55/9, and 65/6) were predicted using a single compartment mass balance model and compared to regulatory or guideline limits. Scented candles may be responsible for indoor acrolein concentrations that could become relevant to health only in the case of chronic exposure. Indoor concentrations of fine PM and SO2 emitted from 65/6 wax burning under worst-case environmental and behavioral conditions were greater than their respective acute guideline limits. However, other waxes had levels of PM and SO2 well below the recommended values. Indoor concentrations of nitrogen dioxide emitted from raw wax burning should be further investigated. The degree of pureness of raw waxes significantly affected the predicted indoor concentrations of PM and SO2. In particular, 65/6 wax was criticized for its high content of impurities.

Airborne particulate matter in school classrooms of northern Italy.

Indoor size-fractioned particulate matter (PM) was measured in seven schools in Milan, to characterize their concentration levels in classrooms, compare the measured concentrations with the recommended guideline values, and provide a preliminary assessment of the efficacy of the intervention measures, based on the guidelines developed by the Italian Ministry of Healthand applied to mitigate exposure to undesirable air pollutants. Indoor sampling was performed from Monday morning to Friday afternoon in three classrooms of each school and was repeated in winter 2011–2012 and 2012–2013. Simultaneously, PM2.5 samples were also collected outdoors. Two different photometers were used to collect the PM continuous data, which were corrected a posteriori using simultaneous gravimetric PM2.5 measurements. Furthermore, the concentrations of carbon dioxide (CO2) were monitored and used to determine the Air Exchange Rates in the classrooms. The results revealed poor IAQ in the school environment. In several cases, the PM2.5 and PM10 24 h concentrations exceeded the 24 h guideline values established by the World Health Organization (WHO). In addition, the indoor CO2 levels often surpassed the CO2 ASHRAE Standard. Our findings confirmed that important indoor sources (human movements, personal clouds, cleaning activities) emitted coarse particles, markedly increasing the measured PM during school hours. In general, the mean PM2.5 indoor concentrations were lower than the average outdoor PM2.5 levels, with I/O ratios generally <1. Fine PM was less affected by indoor sources, exerting a major impact on the PM1–2.5 fraction. Over half of the indoor fine particles were estimated to originate from outdoors. To a first approximation, the intervention proposed to reduce indoor particle levels did not seem to significantly influence the indoor fine PM concentrations. Conversely, the frequent opening of doors and windows appeared to significantly contribute to the reduction of the average indoor CO2 levels.