Atmospheric peroxyacetyl nitrate (PAN) and ozone (O₃) are two typical indicators for photochemical pollution that have adverse effects on the ecosystem and human health. Observation networks for these pollutants have been expanding in developed regions of China, such as North China Plain (NCP) and Pearl River Delta (PRD), but are sparse in Yangtze River Delta (YRD), meaning their concentration and influencing factors remain poorly understood. Here, we performed a one-year measurement of atmospheric PAN, O₃, particulate matter with aerodynamic diameter smaller than 2.5 μm (PM₂.₅), nitrogen oxides (NOₓ), carbon monoxide (CO), and meteorological parameters from December 2016 to November 2017 in Shanghai. Overall, high hourly maximum PAN and O₃ were found to be 7.0 and 185 ppbv in summer, 6.2 and 146 ppbv in autumn, 5.8 and 137 ppbv in spring, and 6.0 and 76.7 ppbv in winter, respectively. Continental air masses probably carried atmospheric pollutants to the sampling site, while frequent maritime winds brought in less polluted air masses. Furthermore, positive correlations (R: 0.72–0.85) between PAN and O₃ were found in summer, indicating a predominant role of photochemistry in their formation. Unlike in summer, weak or no correlations between PAN and O₃ were featured during the other seasons, especially in winter, due to their different loss pathways. Unexpectedly, positive correlations between PAN and PM₂.₅ were found in all seasons. During summer, moderate correlation could be attributed to the strong photochemistry acting as a common driver in the formation of secondary aerosols and PAN. During winter, high PM₂.₅ might promote PAN production through HONO production, hence resulting in a good positive correlation. Additionally, the loss of PAN by thermal decomposition (TPAN) only accounted for a small fraction (ca. 1%) of the total (PAN + TPAN) during a typical winter episode, while it significantly reached 14.4 ppbv (71.1% of the total) in summer.

Limited data were on the acute respiratory responses in the elderly in response to personal exposure of particulate matter (PM). In order to evaluate the changes of airway inflammation and pulmonary functions in the elderly in response to individual exposure of particles (PM₁.₀, PM₂.₅ and PM₁₀), we analyzed 43 elderly subjects with either asthma, chronic obstructive pulmonary disease (COPD) or Asthma COPD Overlap (ACO) and 40 age-matched subjects without asthma nor COPD in an urban community in Shanghai, China. Data were collected at the baseline and in 6 follow-ups from August 2016 to December 2018, once every 3 months except for the last twice with a 6-month interval. In each follow-up, pulmonary functions, fractional exhaled nitric oxide (FeNO), 7-day continuous personal exposure to airborne particles were measured. Multivariate linear mixed effect regression models were applied to investigate the quantitative changes of pulmonary functions and FeNO in two respective groups. The results showed that on average 4.7 follow-up visits were completed in each participant. In subjects with CRDs, an inter-quartile range (IQR) increase of personal exposure to PM₁.₀, PM₂.₅ and PM₁₀ was significantly associated with an average increase of FeNO(Lag1) of 6.7 ppb (95%CI 1.2, 9.9 ppb), 6.2 ppb (95%CI 1.5, 12.0 ppb) and 5.6 ppb (95%CI 1.5, 11.0 ppb), respectively, and an average decrease of FEV1(Lag2) of −3.6 L (95%CI -6.0, −1.1 L), −3.6 L (95%CI -6.4, −0.8 L) and −3.2 L (95%CI -5.8, −0.6 L), respectively, in the single-pollutant model. These associations remained consistent in the two-pollutant models adjusting for gaseous air pollutants. Stratified analysis showed that subjects with lower BMI, females and non-allergies were more sensitive to particle exposure. No robust significant effects were observed in the subjects without CRDs. Our study provided data on the susceptibility of the elderly with CRDs to particle exposure of PM₁.₀ and PM₂.₅, and the modification effects by BMI, gender and history of allergies.

Exposure to outdoor fine particulate matter (PM₂.₅)-bound polycyclic aromatic hydrocarbons (PAHs) is linked to reproductive dysfunction. However, it is unclear which component of PAHs is responsible for the adverse outcomes. In the Male Reproductive Health in Chongqing College Students (MARHCS) cohort study, we measured the exposure levels of 16 PAHs by collecting air PM₂.₅ particles and assessed eight PAHs metabolites from four parent PAHs, including naphthalene, fluorene, phenanthrene, and pyrene in urine samples. We investigated compositional profiles and variation characteristics for 16 PAHs in PM₂.₅, and then assessed the association between PAHs exposure and semen routine parameters, sperm chromatin structure, and serum hormone levels in 1452 samples. The results showed that naphthalene (95% CI: −17.989, −8.101), chrysene (95% CI: −64.894, −47.575), benzo[a]anthracene (95% CI: −63.227, −45.936) and all the high molecular weight (HMW) PAHs in PM₂.₅ were negatively associated with sperm normal morphology. Most of the low molecular weight (LMW) PAHs, such as acenaphthylene, fluorene, phenanthrene, fluoranthene, pyrene, chrysene, benzo[a]anthracene, ∑LMW PAHs and ∑16 PAHs, were correlated with increased sperm motility (all corrected P < 0.05). On the other hand, sperm normal morphology was all negatively associated with urinary metabolites of ∑OH-Nap (95% CI: −5.611, −0.536), ∑OH-Phe (95% CI: −5.741, −0.957), and ∑OH-PAHs (95% CI: −5.274, −0.361). Urinary concentrations of ∑OH-PAHs were found to be negatively associated with sperm high DNA stainability (HDS) (P = 0.023), while ∑OH-Phe were negatively associated with serum testosterone level and sperm HDS (P = 0.004). Spearman correlation analysis showed that except for the urinary OH-Nap metabolites, the rest of the urinary OH-PAHs metabolites were negatively correlated with their parent PAHs in air. The results of this study suggest that various PAHs’ components may affect reproductive parameters differently. Inhalation of PAHs in air, especially HMW PAHs, may be a potential risk factor for male reproductive health.

Ozone (O₃) is a harmful pollutant when present in the lowermost layer of the atmosphere. Therefore, the European Commission formulated directives to regulate O₃ concentrations in near-surface air. However, almost 50% of the 5068 air quality stations in Europe do not monitor O₃ concentrations. This study aims to provide a hybrid modeling system that fills these gaps in the hourly surface O₃ observations on a site scale with much higher accuracy than existing O₃ models. This hybrid model was developed using estimations from multiple linear regression-based eXtreme Gradient Boosting Machines (MLR-XGBM) and O₃ reanalysis from European regional air quality models (CAMS-EU). The binary classification of extremely high O₃ events and the 1- and 24-h forecasts of hourly O₃ were investigated as secondary aims. In this study thirteen stations in Northern Bavaria, out of which six do not monitor O₃, were chosen as test sites. Considering the computational complexity of machine learning algorithms (MLAs), we also applied two recent MLA interpretation methods, namely SHapley Additive exPlanations (SHAP) and Local interpretable model-agnostic explanations (LIME).With SHAP, we showed an increasing effect of temperature on O₃ concentrations which intensifies for temperatures exceeding 17 °C. According to LIME, O₃ concentration peaks are mainly governed by meteorological factors under dry and warm conditions on a regional scale, whereas local nitrogen oxide concentrations control base O₃ concentrations during cold and wet periods.While recently developed MLAs for the spatial estimation of hourly O₃ concentrations had a station-based root-mean-square error (RMSE) above 27 μg/m³, our proposed model significantly reduced the estimation errors by about 66% with an RMSE of 9.49 μg/m³. We also found that logistic regression (LR) and MLR-XGBM performed best in the site-scale classification and 24-h forecast of O₃ concentrations (with a station-averaged accuracy and RMSE of 0.95 and 19.34 μg/m³, respectively).

The number of deaths from air pollution worldwide is estimated at 8.8 million per year, more than the number of deaths from smoking. Air pollutants, such as PM₂.₅, are known to induce respiratory and cardiovascular diseases by inducing oxidative stress. Thioredoxin (Trx) is a 12-kDa endogenous protein that exerts antioxidant activity by promoting dithiol disulfide exchange reactions. We previously synthesized human serum albumin-fused thioredoxin (HSA-Trx), which has a longer half-life in plasma compared with Trx, and demonstrated its efficacy against various diseases including respiratory diseases. Here, we examined the effect of HSA-Trx on urban aerosol-induced lung injury in mice. Urban aerosols induced lung injury and inflammatory responses in ICR mice, but intravenous administration of HSA-Trx markedly inhibited these responses. We next analyzed reactive oxygen species (ROS) production in murine lungs using an in vivo imaging system. The results show that intratracheal administration of urban aerosols induced ROS production that was inhibited by intravenously administered HSA-Trx. Finally, we found that HSA-Trx inhibited the urban aerosol-induced increase in levels of neutrophilic extracellular trap (NET) indicators (i.e., double-stranded DNA, citrullinated histone H3, and neutrophil elastase) in bronchoalveolar lavage fluid (BALF). Together, these findings suggest that HSA-Trx prevents urban aerosol-induced acute lung injury by suppressing ROS production and neutrophilic inflammation. Thus, HSA-Trx may be a potential candidate drug for preventing the onset or exacerbation of lung injury caused by air pollutants.

Air pollution has been an important risk factor for female reproductive health. However, epidemiological evidence of ambient air pollution on the predictor for ovarian reserve (antral follicle count, AFC) is deficient. We aim to comprehensively evaluate the association of long-term exposure to ambient air pollution with AFC among women of reproductive age in Shanxi of north China. 600 women with spontaneous menstrual cycle, not using controlled ovarian stimulation, were enrolled in the retrospective study. Two distinct periods of antral follicle development were designed as exposure windows. Generalized linear model was employed to estimate the change of AFC associated with exposure of atmospheric pollutants (SO₂, NO₂, PM₁₀, PM₂.₅, CO and O₃). Stratification analysis based on age (<30, ≥30 years), university degree (yes, no), years of exposure (2013–2016, 2017–2019) and duration of infertility (<2, 2–5, >5 years) along with two pollutants model were employed to further illustrate the association. We found every 10 μg/m³ increase in SO₂ concentration level during the entire development stage of antral follicle was associated with a −0.01 change in AFC (95% confidence interval: −0.016, −0.002) adjusting for the confounders including age, BMI, parity and infertility diagnosis factors. The significant association of increased SO₂ level with decreased AFC was particularly observed during the early transition from primary follicle to preantral follicle stage by 10 μg/m³ increase in SO₂ exposure level with a −0.01 change (95% CI: -0.015, −0.002) in AFC. The negative association was pronounced among women aged ≥30 years old, and also significant in two pollutants model after adjusting the confounders. No significant associations between other air pollutants and AFC were observed. Our finding suggests that long-term exposure to air pollutant SO₂ is associated with lower AFC, raising our concern that atmospheric SO₂ exposure may have potential adverse impact on women ovarian reserve.

Environmental exposures are one of the greatest threats to human health, yet we lack tools to answer simple questions about our exposures: what are our personal exposure profiles and how do they change overtime (external exposome), how toxic are these chemicals, and what are the sources of these exposures? To capture variation in personal exposures to airborne chemicals in the gas and particulate phases and identify exposures which pose the greatest health risk, wearable exposure monitors can be deployed. In this study, we deployed passive air sampler wristbands with 84 healthy participants (aged 60–69 years) as part of the Biomarkers for Air Pollutants Exposure (China BAPE) study. Participants wore the wristband samplers for 3 days each month for five consecutive months. Passive samplers were analyzed using a novel gas chromatography high resolution mass spectrometry data-processing workflow to overcome the bottleneck of processing large datasets and improve confidence in the resulting identified features. The toxicity of chemicals observed frequently in personal exposures were predicted to identify exposures of potential concern via inhalation route or other routes of airborne contaminant exposure. Three exposures were highlighted based on elevated toxicity: dichlorvos from insecticides (mosquito/malaria control), naphthalene partly from mothballs, and 183 polyaromatic hydrocarbons from multiple sources. Other exposures explored in this study are linked to diet and personal care products, cigarette smoke, sunscreen, and antimicrobial soaps. We highlight the potential for this workflow employing wearable passive samplers for prioritizing chemicals of concern at both the community and individual level, and characterizing sources of exposures for follow up interventions.

Seven perfluorinated and polyfluorinated substances (PFASs), namely perfluorononanoic acid (PFNA), perfluorodecanoic acid (PFDA), perfluorooctanoic acid (PFOA), perfluorooctane sulfonic acid (PFOS), perfluoroheptanoic acid (PFHpA), perfluorohexanoic acid (PFHxA), and perfluoro-1,10-decanedicarboxylic acid (PFDDA), were evaluated in urine and hair samples from children (age: 4–6 years, N = 53), airborne particles sampled at 17 kindergartens, and tap water and bottled water samples. All samples were collected in Hong Kong. The analytical results suggested widespread PFAS contamination. All target PFASs were detected in at least 32% of urine samples, with geometric mean (GM) concentrations ranging from 0.18 to 2.97 ng/L, and in 100% of drinking water samples at GM concentrations of 0.18–21.1 ng/L. Although PFOS and PFDDA were not detected in hair or air samples, the other target PFASs were detected in 48–70% of hair samples (GM concentrations: 2.40–233 pg/g) and 100% of air samples (GM concentrations: 14.8–536.7 pg/m³). In summary, the highest PFAS concentrations were detected in airborne particles measured in kindergartens. PFOA was the major PFAS detected in hair, urine, and drinking water samples, while PFOA, PFDA, and PFHpA were dominant in airborne particles. Although a significant difference in PFAS concentrations in hair samples was observed between boys and girls (p < .05), no significant sex-related difference in urinary PFAS or paired PFAS (hair/urine) concentrations was observed.

Benzothiazoles (BTHs), benzotriazoles (BTRs), and benzenesulfonamides (BSAs) are chemicals used in several industrial and household applications. Despite these compounds are emerging pollutants, there is still a lack of information about their presence in outdoor air samples. In this paper, we developed a new method for the quantification of BTHs, BTRs, and BSAs in airborne particulate matter (PM₁₀). The extraction of fourteen analytes from PM₁₀ was accomplished by microwave-assisted extraction (MAE) using an environmentally friendly mixture of water and ethanol. SPME was used to analyze the target compounds from the MAE extract by gas chromatography-tandem mass spectrometry (SPME-GC-MS/MS), eliminating additional sample clean-up steps. The best working conditions for MAE and SPME were examined multivariately by experimental design techniques. The target compounds were quantified in selected reaction monitoring acquisition mode. The proposed method was carefully validated, and the achieved results were satisfactory in terms of linearity, lower limit of quantification (picograms per cubic meter), intra- and inter-day accuracy (81–118% and 82–114%, respectively), and precision (repeatability and reproducibility in the range 2.3–17% and 7.4–19%, respectively). The application in a real monitoring campaign showed that the developed protocol is a valuable and eco-friendly alternative to the methods proposed so far.

Nitrogen dioxide (NO₂) is an important air pollutant and highly related to air quality, short- and long-term health effects, and even climate. A national model was developed using the extreme gradient boosting algorithm with high-resolution tropospheric vertical column NO₂ densities from the Sentinel-5 Precursor/Tropospheric Monitoring Instrument and general meteorological variables as input to generate daily mean surface NO₂ concentrations across mainland China. Model-derived daily NO₂ estimates were high accuracy with sample-based cross-validation coefficient of determination of 0.83, a root-mean-square error of 7.58 μg/m³, a mean prediction error of 5.56 μg/m³, and a mean relative prediction error of 18.08%. It has good performance in NO₂ estimations at both regional and individual site scale. The model also performed well in terms of estimating monthly, seasonal, and annual mean NO₂ concentrations across China. The model performance appears to better than or comparable to most previous related studies. The seasonal and annual spatial distributions of surface NO₂ across China and several regional NO₂ hotspots in 2019 were derived from the model and analyzed. Also evaluated were the population exposure levels of NO₂ for cities in and provinces of China. At the national scale, about 12% of the population experienced annual mean NO₂ concentrations exceeding the Chinese national air quality standard. The nationwide model with conventional predictors developed here can derive high-resolution surface NO₂ concentrations across China routinely, benefitting air epidemiological and environmental related studies.