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.

The flame retardants hexabromobenzene (HBB) and pentabromobenzene (PBB) have been extensively used and become ubiquitous pollutants in the aquatic environment and biota, but their potential toxic effects on wildlife remained unknown. In this study, by using zebrafish (Danio rerio) as a model, the bioconcentration and developmental neurotoxicity were investigated. Zebrafish embryos were exposed to HBB and PBB (0, 30, 100 and 300 μg/L) from 2 until 144 h post-fertilization (hpf). Chemical analysis showed bioconcentrations of both chemicals, while HBB is readily metabolized to PBB in zebrafish larvae. Embryonic exposure to both chemicals did not cause developmental toxicity, but induced locomotor behavioral anomalies in larvae. Molecular docking results indicated that both chemicals could bind to zebrafish acetylcholinesterase (AChE). Furthermore, HBB and PBB significantly inhibited AChE activities, accompanied by increased contents of acetylcholine and decreased choline in larvae. Downregulation of the genes associated with central nervous system (CNS) development (e.g., mbp, α1-tubulin, gfap, shha) as well as the corresponding proteins (e.g., Mbp, α1-Tubulin) was observed, but gap-43 was upregulated at both gene and protein levels. Together, our results indicate that both HBB and PBB exhibit developmental neurotoxicity by affecting various parameters related to CNS development and indications for future toxicological research and risk assessment of the novel brominated flame retardants.

Inorganic arsenic (iAs) is a naturally occurring metalloid present in drinking water and polluted air exposing millions of people globally. Epidemiological studies have linked iAs exposure to the development of numerous diseases including cognitive impairment, cardiovascular failure and cancer. Despite intense research, an effective therapy for chronic arsenicosis has yet to be developed. Laboratory studies have been of great benefit in establishing the pathways involved in iAs toxicity and providing insights into its mechanism of action. However, the in vivo analysis of arsenic toxicity mechanisms has been difficult by the lack of reliable in vivo biomarkers of iAs’s effects. To address this issue we have applied the use of our recently developed stress reporter models to study iAs toxicity. The reporter mice Hmox1 (oxidative stress/inflammation; HOTT) and p21 (DNA damage) were exposed to iAs at acute and chronic, environmentally relevant, doses. We observed induction of the oxidative stress reporters in several cell types and tissues, which was largely dependent on the activation of transcription factor NRF2. We propose that our HOTT reporter model can be used as a surrogate biomarker of iAs-induced oxidative stress, and it constitutes a first-in-class platform to develop treatments aimed to counteract the role of oxidative stress in arsenicosis. Indeed, in a proof of concept experiment, the HOTT reporter mice were able to predict the therapeutic utility of the antioxidant N-acetyl cysteine in the prevention of iAs associated toxicity.

People use a particulate respirator in order to reduce exposure to ambient fine particulate matter (PM₂.₅). Acute exposure to PM₂.₅ is known to increase blood pressure. However, systematic reviews or meta-analyses on blood pressure-related benefits of using a particulate respirator is lacking. Therefore, we reviewed randomized crossover intervention studies on blood pressure-related effects of particulate matter respirator use. We conducted a literature review of articles found on Embase, Medline, and Cochrane library on August 31, 2020. The study outcomes were systolic and diastolic blood pressure and mean arterial pressure. A random-effect model was used in the meta-analysis. Subgroup analyses, based on age (adult < 60 years, elderly ≥ 60 years), personal PM₂.₅ exposure levels (High: ≥ 25 μg/m³, Low: < 25 μg/m³), and types of monitoring methods (ambulatory and resting blood pressure) were conducted. We identified 297 references, and seven studies were included in our systematic review. None of the studies used a sham respirator as control and complete allocation concealment and blinding were impossible. The use of a particulate respirator was associated with a −1.23 mmHg (95% confidence interval (CI): −2.53, 0.07) change in systolic blood pressure and a −1.57 mmHg (95% CI: −3.85, 0.71) change in mean arterial pressure. There were significant heterogeneities and possibilities for publication bias. The subgroup analyses revealed that studies involving elderly individuals, those conducted in high PM₂.₅ personal exposure, and those in which resting blood pressure was monitored demonstrated a larger decrease in blood pressure resulting from respirator use. Further intervention studies with a large sample size and subjects with diverse characteristics and different personal PM₂.₅ levels may add the evidence to current literature.

As emerging pollutants, microplastics (MPs) have been found globally in various freshwater and marine matrices. This study recompiled 270 endpoints of 3765 individuals from 43 publications, reporting the onset of enhanced biological performance and reduced oxidative stress biomarkers induced by MPs in aquatic organisms at environmentally relevant concentrations (≤1 mg/L, median = 0.1 mg/L). The stimulatory responses of consumption, growth, reproduction and survival ranged from 131% to 144% of the control, with a combined response of 136%. The overall inhibitory response of 9 oxidative stress biomarkers was 71% of the control, and commonly below 75%. The random-effects meta-regression indicated that the extents of MPs-induced responses were independent of habitat, MP composition, morphology, particle size and exposure duration. The results implied that the exposure to MPs at low and high concentrations might induce opposite/non-monotonic responses in aquatic biota. Correspondingly, the hormetic dose response relationships were found at various endpoints, such as reproduction, genotoxicity, immunotoxicity, neurotoxicity and behavioral alteration. Hormesis offers a novel perspective for understanding the dose response mode of aquatic organisms exposed to low and high concentrations of MPs, highlighting the necessity to incorporate the hormetic dose response model into the ecological/environmental risk assessment of MPs.

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.

Finding the potential environmental obesogens is crucial to explain the prevalence of obesity and the related pathologies. Increasing evidence has showed that many chemicals with endocrine disrupting effects can disturb lipid metabolism. Whether 4-hexylphenol (4-HP), a widely-used surfactant and a potential endocrine disrupting chemical (EDC), is associated to influence adipogenesis and hepatic lipid accumulation remained to be elucidated. In this study, both the 3T3-L1 differentiation model and oleic acid (OA)-treated HepG2 cells were used to investigate the effects of 4-HP on lipid metabolism, and the underlying estrogen receptor (ER)-involved mechanism was explored using MVLN assay, molecular docking simulation and the antagonist test. The results based on lipid droplet staining and triglyceride accumulation assay showed that 4-HP treatment promoted the adipogenic differentiation of 3T3-L1 cells and increased hepatic cellular OA accumulation in exposure concentration-dependent manners. The study on the elaborated transcription networks indicated that 4-HP activated peroxisome proliferator-activated receptor γ (PPARγ) as well as the subsequent adipogenic gene program in 3T3-L1 cells. This chemical also induced the increase of OA uptake and decreases of de novo lipogenesis and fatty acid oxidation in HepG2 cells. The agonistic activity of 4-HP in triggering ER-mediated pathway was shown to correlate with its perturbation in lipid metabolism, as evidenced by the enhanced development of mature lipid-laden adipocytes and suppression of excessive hepatic lipid accumulation upon its co-treatment with ER antagonist. Altogether, these findings provide new insights into the potential health impacts of 4-HP exposure as it may relate to obesity and nonalcoholic fatty liver disease.

As the ubiquitous active components in aquatic environments, low molecular weight organic acids (LMWOAs) have a large influence on the environmental behaviors of contaminants. This research was focused on the effect of different LMWOAs including 11 aliphatic acids and 7 aromatic acids on the photodegradation kinetics of tetracycline (TC), and the development of quantitative structure-activity relationship (QSAR) model. Results showed that TC photodegradation in the presence of LMWOAs fitted pseudo-first-order photolysis kinetics, and the observed photolysis rate constant (kobs) varied from 0.077 to 0.331 h⁻¹. The QSAR model was developed by partial-least-squares (PLS) with using a sequential approach with 25 theoretical molecular descriptors. Four descriptors including ELUMO-EHOMO, ELUMO, CCR and Qmax were found to mechanistically and statistically affect kobs.The high cross validated regression coefficient (Qcum2, 0.898) and high correlation coefficient (R², 0.908) indicated significantly goodness-of-fit and high robustness of the model. The predicted and observed values with high agreement in the defined applicability domain featured accuracy and feasibility of model. This work provided a robust predictive method for estimating the TC photodegradation in the presence of different structures of LMWOAs.

The assessment of premature mortality associated with the dramatic changes in fine particulate matter (PM₂.₅) and ozone (O₃) has important scientific significance and provides valuable information for future emission control strategies. Exposure data are particularly vital but may cause great uncertainty in health burden assessments. This study, for the first time, used six methods to generate the concentration data of PM₂.₅ and O₃ in China between 2014 and 2018, and then quantified the changes in premature mortality due to PM₂.₅ and O₃ using the Environmental Benefits Mapping and Analysis Program-Community Edition (BenMAP-CE) model. The results show that PM₂.₅-related premature mortality in China decreases by 263 (95% confidence interval (CI95): 142–159) to 308 (CI95: 213–241) thousands from 2014 to 2018 by using different concentration data, while O₃-related premature mortality increases by 67 (CI95: 26–104) to 103 (CI95: 40–163) thousands. The estimated mean changes are up to 40% different for the PM₂.₅-related mortality, and up to 30% for the O₃-related mortality if different exposure data are chosen. The most significant difference due to the exposure data is found in the areas with a population density of around 10³ people/km², mostly located in Central China, for both PM₂.₅ and O₃. Our results demonstrate that the exposure data source significantly affects mortality estimations and should thus be carefully considered in health burden assessments.

Alberta’s oil sands tailings ponds are suspected to be a source of fugitive emissions of polycyclic aromatic compounds (PACs) to the atmosphere. Here we report, for the first time, fluxes of 6 parent and 21 alkylated PACs based on the measured co-located air and water concentrations using a two-film fugacity-based model (FUG), an inverse dispersion model (DISP) and a simple box model (BOX). Air samples were collected at the Suncor Tailings Pond 2/3 using a high volume air sampler from the “pond” and towards the pond (“non-pond”) directions separately. Mean ∑₂₇PACs in air from the “pond” direction was greater than the “non-pond” direction by a factor of 17. Water-air fugacity ratio of 20 PACs quantifiable in water indicated net volatilization from water. Dispersion and box model results also indicated upward fluxes of 22 PACs. Correlation between the estimated flux results of BOX and DISP model was statistically significant (r = 0.99 and p < 0.05), and correlation between FUG and DISP results ranged from 0.54 to 0.85. In this first-ever assessment of PAC fluxes from tailings pond, the three models confirmed volatilization fluxes of PACs indicating Suncor Tailings Pond 2/3 is a source of PAC emissions to the atmosphere. This study addressed a key data gap identified in the Joint Oil Sands Monitoring Emissions Inventory Compilation Report (Government of Alberta and Canada, 2016) which is the lack of consistent real-world tailings pond fugitive emission monitoring of organic chemicals. Our findings highlight the need for measurements from other tailings ponds to determine their overall contribution in releasing PACs to the atmosphere. This paper presents a practical method for estimating PAC emissions from other tailings ponds, which can provide a better understanding of these fugitive emissions, and thereby help to improve the overall characterization of emissions in the oil sands region.