BACKGROUND: Uncertainty remains about the long-term effects of air pollutants (AP) on multiple diseases, especially subtypes of cardiovascular disease (CVD). We aimed to assess the individual and joint associations of fine particulate matter (PM2.5), along with its chemical components, nitrogen dioxide (NO2) and ozone (O3), with risks of 32 health conditions.
METHODS: A total of 17,566 participants in Sichuan Province, China, were included in 2018 and followed until 2022, with an average follow-up period of 4.2 years. The concentrations of AP were measured using a machine-learning approach. The Cox proportional hazards model and quantile g-computation were applied to assess the associations between AP and CVD.
RESULTS: Per interquartile range (IQR) increase in PM2.5 mass, NO2, O3, nitrate, ammonium, organic matter (OM), black carbon (BC), chloride, and sulfate were significantly associated with increased risks of various conditions, with hazard ratios (HRs) ranging from 1.06 to 2.48. Exposure to multiple air pollutants was associated with total cardiovascular disease (HR 1.75, 95% confidence intervals (CIs) 1.62-1.89), hypertensive diseases (1.49, 1.38-1.62), cardiac arrests (1.52, 1.30-1.77), arrhythmia (1.76, 1.44-2.15), cerebrovascular diseases (1.86, 1.65-2.10), stroke (1.77, 1.54-2.03), ischemic stroke (1.85, 1.61-2.12), atherosclerosis (1.77, 1.57-1.99), diseases of veins, lymphatic vessels, and lymph nodes (1.32, 1.15-1.51), pneumonia (1.37, 1.16-1.61), inflammatory bowel diseases (1.34, 1.16-1.55), liver diseases (1.59, 1.43-1.77), type 2 diabetes (1.48, 1.26-1.73), lipoprotein metabolism disorders (2.20, 1.96-2.47), purine metabolism disorders (1.61, 1.38-1.88), anemia (1.29, 1.15-1.45), sleep disorders (1.54, 1.33-1.78), renal failure (1.44, 1.21-1.72), kidney stone (1.27, 1.13-1.43), osteoarthritis (2.18, 2.00-2.39), osteoporosis (1.36, 1.14-1.61). OM had max weights for joint effects of AP on many conditions.
CONCLUSIONS: Long-term exposure to increased levels of multiple air pollutants was associated with risks of multiple health conditions. OM accounted for substantial weight for these increased risks, suggesting it may play an important role in these associations.

Ambient air pollution has been reported to be a risk factor for hypertensive disorders of pregnancy (HDP). Past studies have reported supportive evidence, but evidence from China is scarce and does not integrate the different periods of the pregnancy course. In this study, 1945 pregnant women with HDP and healthy pregnancies between 2016 and 2022 from the Renmin Hospital of Wuhan University registry network database were analysed. The geographic information, biological information and demographic information of the case were fused in the analysis. Machine learning methods were used to obtain the weight of the variable. Then, we used the generalized linear mixed model to evaluate the relationship between increased exposure to each pollutant at different periods of HDP and examined it in different groups. The results showed that SO2 had the predominate impact (12.65 %) on HDP compared with other air pollutants. SO2 exposure was associated with an increased risk of HDP. Increased unit SO2 concentrations were accompanied by an increased risk of HDP (OR = 1.33, 95 % CI: 1.13, 1.566), and the susceptible window for this effect was mainly in the first trimester (OR = 1.242, 95 % CI: 1.092, 1.412). In addition, SO2 exposure was associated with an increased risk of HDP in urban maternity (OR = 1.356, 95 % CI: 1.112, 1.653), obese maternity (OR = 3.58, 95 % CI: 1.608, 7.971), no higher education maternity (OR = 1.348, 95 % CI: 1.065, 1.706), nonzero delivery maternity (OR = 1.981, 95 % CI: 1.439, 2.725), maternal with first time maternity (OR = 1.247, 95 % CI: 1.007, 1.544) and other groups. In summary, SO2 exposure in early pregnancy is one of the risk factors for HDP, and the increased risk of HDP due to increased SO2 exposure may be more pronounced in obese, urban, low-education, and nonzero delivery populations.

In the troposphere, ozone (O3) formation can be limited by NOx, VOCs, or both, complicating efforts to reduce O3 by controlling its precursors. This study used formaldehyde (HCHO) data and nitrogen dioxide (NO2) data from the Ozone Monitoring Instrument (OMI) to analyze O3 formation sensitivity in Fujian from 2012 to 2021. Over the past decade, an 8.7% reduction in NO2 VCDs and a 9.91% increase in HCHO VCDs were observed. Due to differences in the primary driving factors, HCHO VCDs exhibit a characteristic seasonal pattern with higher in summer and lower in winter, whereas NO2 VCDs show the opposite trend. O3 formation chemistry was accurately diagnosed by combining satellite-based data and ground-based O3 data. A new threshold value (3.3-4.6) was derived to determine the transition from VOC-limited to NOx-limited O3 formation regimes. Results showed that O3 sensitivity exhibited pronounced seasonal variations. The VOC-limited regime predominates throughout the entire Fujian region in winter, whereas it occupies only 5% of the area in summer. A VOC-limited region was found widely across Fujian on an annual average, but it decreased by 24% over 10 years. Transitional areas experienced a 19% increase. In two natural emission reduction cases (reductions during the Chinese Lunar New Year holiday and reductions in weekend traffic emissions compared to weekdays), ground-level O3 effectively captured the impacts of sensitivity changes. The impact suggests that when Fujian is in the VOC control region, a significant reduction in NOx, without effective VOC control, might lead to an O3 increase. The importance of controlling VOC emissions is highlighted in Fujian. This study enhances the understanding of O3 formation regimes in southeastern China, which is crucial for developing O3 prevention and control strategies.

UNASSIGNED: Traditional observational studies exploring the association between air pollution and infections have been limited by small sample sizes and potential confounding factors. To address these limitations, we applied Mendelian randomization (MR) to investigate the potential causal relationships between particulate matter (PM2.5, PM2.5-10, and PM10), nitrogen dioxide, and nitrogen oxide and the risks of infections.
UNASSIGNED: Single nucleotide polymorphisms (SNPs) related to air pollution were selected from the genome-wide association study (GWAS) of the UK Biobank. Publicly available summary data for infections were obtained from the FinnGen Biobank and the COVID-19 Host Genetics Initiative. The inverse variance weighted (IVW) meta-analysis was used as the primary method for obtaining the Mendelian randomization (MR) estimates. Complementary analyses were performed using the weighted median method, MR-Egger method, and MR Pleiotropy Residual Sum and Outlier (MR-PRESSO) test.
UNASSIGNED: The fixed-effect IVW estimate showed that PM2.5, PM2.5-10 and Nitrogen oxides were suggestively associated with COVID-19 [for PM2.5: IVW (fe): OR 3.573(1.218,5.288), PIVW(fe) = 0.021; for PM2.5-10: IVW (fe): OR 2.940(1.385,6.239), PIVW(fe) = 0.005; for Nitrogen oxides, IVW (fe): OR 1.898(1.318,2.472), PIVW(fe) = 0.010]. PM2.5, PM2.5-10, PM10, and Nitrogen oxides were suggestively associated with bacterial pneumonia [for PM2.5: IVW(fe): OR 1.720 (1.007, 2.937), PIVW(fe) = 0.047; for PM2.5-10: IVW(fe): OR 1.752 (1.111, 2.767), P IVW(fe) = 0.016; for PM10: IVW(fe): OR 2.097 (1.045, 4.208), PIVW(fe) = 0.037; for Nitrogen oxides, IVW(fe): OR 3.907 (1.209, 5.987), PIVW(fe) = 0.023]. Furthermore, Nitrogen dioxide was suggestively associated with the risk of acute upper respiratory infections, while all air pollution were not associated with intestinal infections.
UNASSIGNED: Our results support a role of related air pollution in the Corona Virus Disease 2019, bacterial pneumonia and acute upper respiratory infections. More work is need for policy formulation to reduce the air pollution and the emission of toxic and of harmful gas.

The mechanisms underlying relationships between ambient air pollution and chronic obstructive pulmonary disease (COPD) risk remained largely uncertain. In this study, we aim to evaluate whether metabolic signature comprising multiple circulating metabolites can characterize metabolic response to the multiple air pollution; and to assess whether the identified metabolic signature contribute to COPD risk. A total of 227,962 participants with complete data were included from the UK biobank study. Concentrations of nitrogen dioxide (NO2), nitrogen oxides (NOx), and particulate matter (PM2.5 and PM10) were evaluated by land-use regression models. We newly computed an air pollution score to reflect joint exposure to multiple air pollutants. Circulating metabolome was quantified by nuclear magnetic resonance (NMR) spectroscopy. During a median of 12.78 years of follow-up, a total of 8685 incident COPD cases were documented. After multiple correction, the Cox regression models showed that 102 of 143 metabolites were significantly associated with COPD risk. Utilizing elastic net regularized regressions, we identified a metabolic signature comprising 106 metabolites (including lipid, fatty acids, glycolysis and amino acids et al.) were robustly related to air pollution score. In the multivariate-adjusted Cox regression models, the derived metabolic signature showed a positive correlation with incident COPD [HR per SD = 1.20 (95% CI: 1.17-1.22)]. Casual mediation analysis further noted that the constructed metabolic signature mediated 10.5 % (8.3%-13.1%) of the air pollution-COPD associations. Taken together, our findings identified a metabolic signature that captured metabolic response to various air pollutants exposure jointly, and predicted future COPD risk independent of known risk factors.

UNASSIGNED: To investigate the association between exposure to atmospheric pollutants and preterm birth in a river valley-type city and its critical exposure windows.
UNASSIGNED: A retrospective cohort study was used to collect data from the medical records of preterm and full-term deliveries in two hospitals in urban areas of a typical river valley-type city from January 2018 to December 2019. A total of 7,288 cases were included in the study with general information such as pregnancy times, the number of cesarean sections, occupation, season of conception and regularity of the menstrual cycle. And confounding factors affecting preterm birth were inferred using the chi-square test. The effects of exposure to each pollutant, including particulate matter 2.5 (PM2.5), particulate matter 10 (PM10), nitrogen dioxide (NO2), sulfur dioxide (SO2), carbon monoxide (CO) and ozone (O3), during pregnancy on preterm birth and the main exposure windows were explored by establishing a logistic regression model with pollutants introduced as continuous variables.
UNASSIGNED: Maternal age, pregnancy times, number of births, number of cesarean sections, season of conception, complications diseases, comorbidities diseases, hypertension disorder of pregnancy and neonatal low birth weight of the newborn were significantly different between preterm and term pregnant women. Logistic regression analysis after adjusting for the above confounders showed that the risk of preterm birth increases by 0.9, 0.6, 2.4% in T2 and by 1.0, 0.9, 2.5% in T3 for each 10 μg/m3 increase in PM2.5, PM10, NO2 concentrations, respectively. The risk of preterm birth increases by 4.3% in T2 for each 10 μg/m3 increase in SO2 concentrations. The risk of preterm birth increases by 123.5% in T2 and increases by 188.5% in T3 for each 10 mg/m3 increase in CO concentrations.
UNASSIGNED: Maternal exposure to PM2.5, PM10, NO2, CO was associated with increased risk on preterm birth in mid-pregnancy (T2) and late pregnancy (T3), SO2 exposure was associated with increased risk on preterm birth in mid-pregnancy (T2).

Nitrogen dioxide (NO2) is a significant environmental and human health hazard. Current NO2 sensors often lack sensitivity and selectivity under ambient conditions. This study investigates ammonia pyrolysis modification of monolayer Ti3C2Tx MXene to enhance NO2 detection at room temperature. Nitrogen-doped Ti3C2Tx demonstrates a substantial improvement in sensitivity, with a response of 8.87% to 50 ppm of NO2 compared to 0.65% for the original sensor, representing a 13.8-fold increase. The nitrogen-doped sensor also exhibits superior selectivity and linearity for NO2 under ambient conditions. Theoretical analysis shows that nitrogen incorporation promotes enhanced interaction between Ti3C2Tx and its surface oxygen-containing functional groups through electronic hybridization, resulting in improved adsorption energy (1.80 |eV|) and electron transfer efficiency (0.67 |e|) for NO2, thereby enhancing its gas-sensing performance. This study highlights the potential of ammonia pyrolysis-treated Ti3C2Tx MXene for advancing NO2 sensor technologies with heightened performance at room temperature.

Short-term exposure to air pollution has previously been studied in relation to certain neurological disorders, but there is still a lack of convincing data linking air pollution to epileptic seizures. The study\'s goal was to investigate how exposure to ambient nitrogen dioxide (NO2) affected the number of patients seeking assistance at the Wuhan Emergency Medical Center due to epileptic seizures. We gathered data on medical emergency calls (MECs), daily ambient air pollution concentrations (SO2, NO2, PM2.5, PM10, CO, and O3), and meteorological variables in Wuhan, China, spanning from January 1, 2017, to November 30, 2019. To investigate the potential influence of ambient nitrogen dioxide on MECs for epileptic seizures, we carried out a time-series investigation using the general additive model (GAM). Additionally, analyses stratified by season, age, and gender were performed. A total of 8989 records of MECs for epileptic seizures were enrolled in our study during the period. Statistical analysis indicates that a rise of 10 μg/m3 in NO2 concentration is linked to a 0.17% increase in daily MECs for epileptic seizures (95% confidence interval [CI]: 0.02%, 0.32%). Furthermore, people aged 14-59 years were more susceptible(2.25%, P < 0.05). The short-term effects of NO2 exposure on daily MECs for epileptic seizures were stronger in warm seasons than in cool seasons (0.55% vs. -0.10%, P < 0.0001). Our findings suggests that short-term exposure to ambient NO2 was positively correlated with daily MECs for epileptic seizures in Wuhan, China. Additionally, we observed that these associations were stronger in patients aged above 14 but under 60 years and the warmer seasons (from April to September).

A significant body of research has documented the profound changes in global atmospheric conditions during the COVID-19 pandemic. However, there is still an inadequate comprehensive comparison and assessment of countries before, during, and after the pandemic. Variations in restriction policies, human behaviors, and national traits lead to significant differences in how restriction policies affect atmospheric pollution. This study focuses on NO2, a pollutant with high temporal sensitivity, and utilizes the Oxford COVID-19 policy stringency index along with demographic information. Through spatial-temporal mapping, we analyzed NO2 emission fluctuations and calculated the emission changes in each country. Drawing from this analysis, we explored the relationships among these factors and found that over the span of 2019-2022, across 193 countries, global NO2 emissions displayed a distinct trajectory: initially decreasing, subsequently rebounding, and eventually fluctuating. Most countries exhibited seasonal variations in NO2 emissions. Additionally, the study uncovered a correlation between the stringency of COVID-19 policies and the reduction in NO2 emissions: as policies became stricter, emissions significantly decreased in most countries. In contrast, in countries with lower population densities, stricter policies paradoxically led to an increase in emissions. These findings underscore the importance of considering demographic factors and geographical context in the formulation and implementation of environmental policies.

This study aimed to investigate the univariate and bivariate effects of ambient temperature and air pollutants on 57,251 inpatients with AECOPD (Acute Exacerbation of Chronic Obstructive Pulmonary Disease) in Ganzhou from January 1, 2016, to December 31, 2019. We categorized the daily mean temperature and air pollutant variables based on the exposure-response curve of the Distributed Lag Non-Linear Model. Poisson regression model was used for interaction and stratification analysis. The Relative Excess Risk due to Interaction (RERI) with 95% confidence intervals (95% CI) between daily mean temperature (Tmean) and air pollutants including NO2, PM2.5, and PM10 were - 0.428 (95% CI - 0.637, - 0.218), -- 0.227 (95% CI - 0.293, - 0.161), and - 0.119 (95% CI - 0.159, - 0.079). Further stratification analysis showed the relative risk (RR) (95% CI) of high NO2 (> 33 μg/m3) at low Tmean (≤ 28 °C) was 1.119 (95% CI 1.096, 1.142). Low temperatures with high PM10 in men and high PM2.5 in women were associated with a higher risk of AECOPD hospitalization. The results indicate a higher risk of hospitalization for AECOPD when there is with high concentrations of air pollution at low temperatures.