Personal exposure to aldehydes and potential health risks among schoolchildren in the city.

Schoolchildren are sensitive to airborne aldehyde exposures. The knowledge regarding inhalation exposure to aldehydes and the factors influencing exposure in schoolchildren is limited. This study aimed to assess the variability and potential health risks of exposure to aldehydes (including formaldehyde) in schoolchildren. The important factors affecting personal exposure to aldehydes were also explored. Forty schoolchildren were recruited from the urban and suburban areas of Taiwan for aldehyde samplings and questionnaire surveys. Personal and indoor home samples of aldehydes were collected simultaneously during warm and cold seasons. We also identified the potential variables associated with aldehyde exposure based on the participant's responses to the questionnaires using mixed-effects models. The dominant three abundant aldehydes identified in personal exposure samples were formaldehyde (geometric mean, GM = 12.2 µg/m3), acetaldehyde (GM = 5.53 µg/m3), and hexaldehyde (GM = 8.79 µg/m3), accounting for approximately 80% of the total selected aldehydes. Higher personal exposure to aldehydes was observed during the warm season. Moreover, the within-subject variance was predominant, accounting for 66.6 to > 99.9% of the total variance in exposure. Schoolchildren had a high probability of overexposure to formaldehyde and acrolein, which resulted in an incremental lifetime cancer risk of 1.59 × 10-4 (95th percentile = 4.64 × 10-4). Season, location, household refurbishment, and indoor ventilation variables were significantly associated with personal exposure to aldehydes. The results can improve our understanding of aldehyde exposure among schoolchildren to propose mitigation strategies. These findings may be applied to further epidemiological studies.

Impacts of COVID-19's restriction measures on personal exposure to VOCs and aldehydes in Taipei City.

The Coronavirus Disease 2019 (COVID-19) pandemic provided an unprecedented natural experiment, that allowed us to investigate the impacts of different restrictive measures on personal exposure to specific volatile organic compounds (VOCs) and aldehydes and resulting health risks in the city. Ambient concentrations of the criteria air pollutants were also evaluated. Passive sampling for VOCs and aldehydes was conducted for graduate students and ambient air in Taipei, Taiwan, during the Level 3 warning (strict control measures) and Level 2 alert (loosened control measures) of the COVID-19 pandemic in 2021-2022. Information on the daily activities of participants and on-road vehicle counts nearby the stationary sampling site during the sampling campaigns were recorded. Generalized estimating equations (GEE) with adjusted meteorological and seasonal variables were used to estimate the effects of control measures on average personal exposures to the selected air pollutants. Our results showed that ambient CO and NO2 concentrations in relation to on-road transportation emissions were significantly reduced, which led to an increase in ambient O3 concentrations. Exposure to specific VOCs (benzene, methyl tert-butyl ether (MTBE), xylene, ethylbenzene, and 1,3-butadiene) associated with automobile emissions were remarkably decreased by ~40-80 % during the Level 3 warning, resulting in 42 % and 50 % reductions of total incremental lifetime cancer risk (ILCR) and hazard index (HI), respectively, compared with the Level 2 alert. In contrast, the exposure concentration and calculated health risks in the selected population for formaldehyde increased by ~25 % on average during the Level 3 warning. Our study improves knowledge of the influence of a series of anti-COVID-19 measures on personal exposure to specific VOCs and aldehydes and its mitigations.

Model development and validation of personal exposure to PM2.5 among urban elders.

Indirect measurements through a combination of microenvironment concentrations and personal activity diaries provide a potentially useful alternative for PM2.5 exposure estimates. This study was to optimize a personal exposure model based on spatiotemporal model predictions for PM2.5 exposure in a sub-cohort study. Personal, home indoor, home outdoor, and ambient monitoring data of PM2.5 were conducted for an elderly population in the Taipei city of Taiwan. The proposed microenvironment exposure (ME) models incorporate PM2.5 measurements and individual time-activity information with a generalized estimating equation (GEE) analysis. We evaluated model performance with daily personal PM2.5 exposure based on the coefficient of determination, accuracy, and mean bias error. Ambient and home outdoor measures as exposure surrogates are likely to under- and overestimate personal exposure to PM2.5 in our study population, respectively. Measured and predicted indoor exposures were highly correlated with personal PM2.5 exposure. The awareness of peculiar smells is an important factor that significantly increases personal PM2.5 exposure by 46-70%. The model incorporating home indoor PM2.5 can achieve the highest agreement (R2 = 0.790) with personal exposure and the lowest measurement error. The ME model with the GEE analysis combining home outdoor PM2.5 determined by LUR model with a machine learning technique can improve the prediction (R2 = 0.592) of personal PM2.5 exposure, compared with the prediction of the traditional LUR model (R2 = 0.385).

Ambient VOCs in residential areas near a large-scale petrochemical complex: Spatiotemporal variation, source apportionment and health risk.

This study investigated ambient volatile organic compounds (VOCs) and assessed excess health risks for child, adult and elderly populations in a residential area near a large-scale petrochemical complex in central Taiwan. A total of 155 daily VOC samples were collected in canisters from nine sites in spring, summer and winter during 2013-2014. We used a positive matrix factorization (PMF) model incorporating a conditional probability function (CPF) to quantify the potential sources of VOCs with the influences of local source directions. We then evaluated the non-cancer and cancer risks of specific VOCs with probabilistic distributions by performing a Monte-Carlo simulation for the child, adult, and elderly populations. Most of the VOCs were higher in summer than in winter or spring for the sampling sites. The presence of vinyl acetate, chloroethene, and 1,2-dichloroethane were significantly high within a 5-km radius of the petrochemical complex. Four potential sources of ambient VOCs, industrial emission (49.2%-63.6%), traffic-related emission (13.9%-19.1%), fuel evaporation (12.3%-16.9%), and aged emission (10.2%-14.8%), were identified. The cancer risk of ambient VOC exposure was mainly attributed to the industrial source in the study area, while the non-cancer risk was of less concern. Benzene associated with fuel evaporation resulted in the highest cancer risk (4.1 × 10-5-5.5 × 10-5) as compared to that of the other toxic VOCs.