Estimations of infiltration factors of diurnal PM2.5 and heavy metals in children's bedrooms

Evaluating the representativeness of atmospheric PM2.5 data for indoor exposure: insights from concentrations, chemical compositions, and sources

Studies relied on atmospheric PM2.5 data to estimate health risks and sources, but its representativeness for indoor air remains unclear. This study placed an atmospheric PM2.5 sampler on the rooftop of a three-story building, and indoor and outdoor (balcony) samples were collected from study houses within a 5 km radius of the atmospheric sampling site during low and high PM2.5 seasons to evaluate the representativeness of atmospheric PM2.5 data. The average PM2.5 concentrations were 15.4 ± 7.1 μg/m3 (indoor), 18.9 ± 7.0 μg/m3 (outdoor), and 13.9 ± 6.1 μg/m3 (atmospheric). Atmospheric PM2.5 concentrations were significantly associated with indoor and outdoor PM2.5, but outdoor PM2.5 concentrations were higher. Source identification revealed that traffic-related emission was a major contributor to PM2.5 across all sites and seasons, while long-range transport from China was another source during the high PM2.5 season based on lead isotope ratios. Crustal elements and construction dust, identified through positive matrix factorization, were higher in both indoor and outdoor air than in the atmosphere. Elements from industrial or traffic emissions showed similar concentrations across different sampling sites. The average ratios of indoor to outdoor or atmospheric PM2.5 concentrations were 0.84 ± 0.27 and 1.18 ± 0.37, respectively. In conclusion, atmospheric PM2.5 can be used to estimate PM2.5 exposure and element concentrations from industrial or traffic emissions in indoors; however, it underestimates the contributions of crustal elements and construction dust. Ambient PM2.5 samples from outdoor or atmospheric environments should be considered when comparing their influence on indoor air across studies.

Impact of agricultural activity on PM2.5 and its compositions in elementary schools near corn and rice farms

Agricultural activity is an important source of particulate matter <2.5 μm in size (PM2.5) in rural areas. In Taiwan, many elementary schools are surrounded by farms, and studies investigating the impact of agricultural activity on air quality in schools are required. We collected PM2.5 samples from the classrooms of elementary schools near corn and rice farms during the crop cultivation stages and analyzed their concentrations and compositions to investigate whether agricultural activity affects the schools' air quality. We found that the average ratio of PM2.5/PM10 (<10 μm in particle size) was <0.6 in the school near the corn farm, and that the indoor PM2.5/PM10 ratio was significantly associated (r = 0.93, p < 0.05) with the outdoor ratio. Moreover, the potassium (K) concentration in the school near the corn farm (189.2 ± 119 ng/m3) was higher than that near the rice farm (140.9 ± 116.0 ng/m3). There were higher concentrations of K and crustal elements, and a greater crustal elements/heavy metals ratio, in the school near the corn farm during the sowing and soil covering stages than during other cultivation stages. Positive matrix factorization (PMF) results indicate that agricultural activity was a predominant contributor of PM2.5 in the schools near corn and rice farms, however, PM2.5 from industrial and traffic emissions also affected schools' air quality. In summary, agricultural activity influenced the air quality of schools, especially near the corn farm. Governments should develop air quality management policies to reduce the risk of children suffering exposure to high particle concentrations in these schools and further suggest that the impact of industrial and traffic emissions on air quality also requires attention.

Investigation of source and infiltration of toxic metals in indoor PM2.5 using Pb isotopes during a season of high pollution in an urban area

Lead (Pb) isotope ratio has been applied in source investigation for particulate matter in size < 2.5 μm. However, arsenic (As) and cadmium (Cd) are carcinogenic to human and their isotope analysis is difficult. This study investigated whether the Pb isotope ratio was a useful indicator in identifying the sources of As and Cd indoors and investigating its influencing factors. This study also calculated the infiltration factor (Finf) for metals to assess the influences of indoor- and outdoor-generated metals to indoor air. The As and Cd concentrations in indoor air were 0.87 ± 0.69 and 0.19 ± 0.15 ng/m3, respectively; the corresponding values for outdoor air were 1.44 ± 0.80 and 0.33 ± 0.19 ng/m3. The Finf of As and Cd were 0.60 ± 0.37 and 0.58 ± 0.39, and outdoor was a predominant contributor to indoor As and Cd. The Pb isotopes ratio indicated that traffic-related emission was a major contributor to Pb. The Pb concentration was associated with those of As and Cd in indoor or outdoor air, as was the 208Pb/207Pb ratio in outdoor air. Significant correlations between indoor 208Pb/207Pb values and As and Cd concentrations in indoor air were found only in study houses with air change rate > 1.5 h-1. These findings suggested that traffic-related emission was identified as a major source of As and Cr. The 208Pb/207Pb is a useful indicator in investigating the source of As and Cd; however, the air change rate influences the applicability of this approach on source identification.

Understanding the time-activity pattern to improve the measurement of personal exposure: An exploratory and experimental research

Although ambient fine particulate matter (PM2.5) concentrations and their components are commonly used as proxies for personal exposure monitoring, developing an accurate and cost-effective method to use these proxies for personal exposure measurement continues to pose a significant challenge. Herein, we propose a scenario-based exposure model to precisely estimate personal exposure level of heavy metal(loid)s (HMs) using scenario HMs concentrations and time-activity patterns. Personal exposure levels and ambient pollution levels for PM2.5 and HMs differed significantly with corresponding personal/ambient ratios of approximately 2, and exposure scenarios could narrow the assessment error gap by 26.1-45.4%. Using a scenario-based exposure model, we assessed the associated health risks of a large sample population and identified that the carcinogenic risk of As exceeded 1 × 10-6, while we observed non-carcinogenic risks from As, Cd, Ni, and Mn in personal exposure to PM2.5. We conclude that the scenario-based exposure model is a preferential alternative for monitoring personal exposure compared to ambient concentrations. This method ensures the feasibility of personal exposure monitoring and health risk assessments in large-scale studies.

Spatial and seasonal variations in the carbon and lead isotopes of PM2.5 in air of residential buildings and their applications for source identification

To understand isotope distributions of PM_2.5 in residential buildings and apply them for source identification, carbon (δ¹³C) and lead (Pb) isotope ratios in indoor and outdoor air of residential buildings were analyzed. Moreover, factor analysis (FA) was employed to investigate sources, which were compared through isotopic analyses. The average δ¹³C values of indoor air are -26.94 ± 1.22‰ and -27.04 ± 0.44‰ in warm (August to October) and cold (February to March) seasons, respectively, and the corresponding values for outdoor air are -26.77 ± 0.54‰ and -26.57 ± 0.39‰. The average ²⁰⁶Pb/²⁰⁷Pb (²⁰⁸Pb/²⁰⁷Pb) ratios of indoor air are 1.1584 ± 0.0091 (2.4309 ± 0.0125) and 1.1529 ± 0.0032 (2.4227 ± 0.0081) in warm and cold seasons, respectively, and the corresponding values for outdoor air are 1.1594 ± 0.0069 (2.4374 ± 0.0103) and 1.1538 ± 0.0077 (2.4222 ± 0.0085). Seasonal variation in δ¹³C values or Pb isotope ratios of indoor air was not significant, and similar results were obtained for outdoor air. Significant differences were not observed between δ¹³C values or Pb isotope ratios of indoor and outdoor air. Traffic emission is the major contributor to indoor and outdoor PM_2.5 based on isotopic analyses; this result was consistent with the results of FA. The δ¹³C values of indoor air in buildings with poor ventilation conditions were significantly lighter than those of outdoor air. In summary, the spatial and seasonal variations of isotopes were similar in residential buildings, which can be used to identify sources of indoor PM_2.5, and ventilation condition is an influencing factor.