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People generally spend most of their time indoors, making a comprehensive evaluation of air pollution characteristics in various indoor microenvironments of great significance for accurate exposure estimation. In this study, field measurements were conducted in Kunming City, Southwest China, using real-time PM2.5 sensors to characterize indoor PM2.5 in ten different microenvironments including three restaurants, four public places, and three household settings. Results showed that the daily average PM2.5 concentrations in restaurants, public spaces, and households were 78.4 ± 24.3, 20.1 ± 6.6, and 18.0 ± 4.3 µg/m3, respectively. The highest levels of indoor PM2.5 in restaurants were owing to strong internal emissions from cooking activities. Dynamic changes showed that indoor PM2.5 levels increased during business time in restaurants and public places, and cooking time in residential kitchens. Compared with public places, restaurants generally exhibit more rapid increases in indoor PM2.5 due to cooking activities, which can elevate indoor PM2.5 to high levels (5.1 times higher than the baseline) in a short time. Furthermore, indoor PM2.5 in restaurants were dominated by internal emissions, while outdoor penetration contributed mostly to indoor PM2.5 in public places and household settings. Results from this study revealed large variations in indoor PM2.5 in different microenvironments, and suggested site-specific measures for indoor PM2.5 pollution alleviation.

People generally spend most of their time indoors, making indoor air quality be of great significance to human health. Large spatiotemporal heterogeneity of indoor air pollution can be hardly captured by conventional filter-based monitoring but real-time monitoring. Real-time monitoring is conducive to change air assessment mode from static and sparse analysis to dynamic and massive analysis, and has made remarkable strides in indoor air evaluation. In this review, the state of art, strengths, challenges, and further development of real-time sensors used in indoor air evaluation are focused on. Researches using real-time sensors for indoor air evaluation have increased rapidly since 2018, and are mainly conducted in China and the USA, with the most frequently investigated air pollutants of PM2.5. In addition to high spatiotemporal resolution, real-time sensors for indoor air evaluation have prominent advantages in 3-dimensional monitoring, pollution peak and source identification, and short-term health effect evaluation. Huge amounts of data from real-time sensors also facilitate the modeling and prediction of indoor air pollution. However, challenges still remain in extensive deployment of real-time sensors indoors, including the selection, performance, stability, as well as calibration of sensors. In future, sensors with high performance, long-term stability, low price, and low energy consumption are welcomed. Furthermore, more target air pollutants are also expected to be detected simultaneously by real-time sensors in indoor air monitoring.

Inhalation exposure to polycyclic aromatic hydrocarbons (PAHs) from indoor solid fuel combustion poses a high health risk, and PAHs bound to particles with smaller sizes (e.g., PM1.0, aerodynamic diameter ≤ 1.0 µm) should be of particular concern since they can penetrate deep into pulmonary alveoli. However, PAHs bound to PM1.0 was less studied compared with PAHs in total suspended particles or PM2.5. In this study, multiple provincial field measurements were conducted to investigate 28 PAHs bound to PM1.0 in rural Chinese homes. Daily averaged PM1.0-PAH28 concentrations ranged from 27 ng/m3 to 3795 ng/m3 (median: 233 ng/m3) and from 10 ng/m3 to 2978 ng/m3 (median: 87 ng/m3) in indoor and outdoor air, respectively. Higher concentrations were found in northern China in winter due to increased solid fuels consumption for space heating. The ambient pollution was lower during the non-heating season in Eastern China, where clean energy was preferred. Highly toxic congeners were more abundant in indoor air compared with outdoor air. The results of source apportionment revealed that solid fuel combustion was the primary contributor to rural household PM1.0-PAHs, but other sources such as vehicles cannot be overlooked. The transition to cleaner energy can reduce the indoor PM1.0-PAH28 and BaPeq-28 concentrations by 87% and 98%, respectively, and more efficient reduction was observed for highly toxic congeners. The estimated Incremental Lifetime Cancer Risk (ILCR) based on PM1.0-PAH28 ranged from 4.6 × 10−5 to 3.4 × 10−2, far exceeding the acceptable level of 10−6. Over 60% of the ILCR could be attributed to inhalation exposure during childhood and adolescence.

Indoor biomass burning produces large amounts of small particles and hazardous contaminants leading to severe air pollution and potentially high health risks associated with inhalation exposure. Personal samplers provide more accurate estimates of inhalation exposure. In this study, inhalation exposure to size-segregated particles and particulate polycyclic aromatic hydrocarbons (PAHs) for the biomass user was studied by deploying personal samplers. The study found that daily PM2.5 inhalation exposure level was as high as 121 ± 96 μg/m3, and over 84% was finer PM1.0. For PAHs, the exposure level was 113 ± 188 ng/m3, with over 77% in PM1.0. High molecular weight PAHs with larger toxic potentials enriched in smaller particles resulting in much high risks associated with PAHs inhalation exposure. Indoor exposure contributed to ~80% of the total inhalation exposure as a result of high indoor air pollution and longer residence spent indoor. The highest exposure risk was found for the male smoker who conducted cooking activities at home.