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Sources, Trigger Points, and Effect Size of Associations between PM2.5-bound Polycyclic Aromatic Hydrocarbons (PAHs) and Fractional Exhaled Nitric Oxide (FeNO): A Panel Study with 16 Follow-up Visits over 4 years

呼出气一氧化氮 环境化学 一氧化氮 环境卫生 化学 环境科学 医学 内科学 有机化学 哮喘 支气管收缩
作者
Yu-Cong Fu,Wenhui Jia,Ningyu Zhang,Zhiyu Wang,Nan Zhang,Tong Wang,Nan Zhang,Jia Xu,Xueli Yang,Qiang Zhang,Changping Li,Xumei Zhang,Wen Yang,Bin Han,Liwen Zhang,Nai-jun Tang,Zhipeng Bai
出处
期刊:Chemosphere [Elsevier BV]
卷期号:360: 142459-142459 被引量:2
标识
DOI:10.1016/j.chemosphere.2024.142459
摘要

Exposure to fine particulate matter (PM2.5) is a significant concern for respiratory health. However, the sources, trigger points, and effect size of specific associations between PM2.5 components, particularly polycyclic aromatic hydrocarbons (PAHs) and the airway inflammatory marker fractional exhaled nitric oxide (FeNO) have not been fully explored. In this study, 69 healthy college students were enrolled and followed up 16 times from 2014 to 2018. Individual FeNO was measured and ambient air PM2.5 samples were collected for 7 consecutive days before each follow-up. PAHs were quantified using Gas Chromatography-Mass Spectrometry. Linear mixed-effect regression models were employed to evaluate the associations between PM2.5-bound PAHs and FeNO. Additionally, PMF (Positive Matrix Factorization) was utilized to identify sources of PM2.5-bound PAHs and assess their impact on FeNO. Throughout the study, the average (SD) of ΣPAHs concentrations was 78.50 (128.9) ng/m3. PM2.5 and PM2.5-bound PAHs were significantly associated with FeNO at various lag days. Single-day lag analyses revealed maximum effects of PM2.5 on FeNO, with an increase of 7.71% (95% CI: 4.67%, 10.83%) per interquartile range (IQR) (48.10 μg/m3) increase of PM2.5 at lag2, and ΣPAHs showed a maximum elevation in FeNO of 6.40% (95% CI: 2.33%, 10.63%) at lag4 per IQR (57.39 ng/m3) increase. Individual PAHs exhibited diversity peak effects on FeNO at lag3 (6 of 17), lag4 (9 of 17) in the single-day model, and lag0-5 (8 of 17) (from lag0-1 to lag0-6) in the cumulative model. Source apportionment indicated coal combustion as the primary contributor (accounting for 30.7%). However, a maximum effect on FeNO (an increase of 21.57% (95% CI: 13.58%, 30.13%) per IQR increase) was observed with traffic emissions at lag4. The findings imply that strategic regulation of particular sources of PAHs, like traffic emissions, during specific periods could significantly contribute to safeguarding public health.
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