Epidemiology and public health concerns have primarily relied on the accurate control of gas pollutants, requiring highly efficient gas sensor devices for detecting hazardous gases. Despite the dedication of many efforts in this era, the precise, continuous scrutiny of gases remains elusive for appropriate gas selectivity, prompt response and recovery time, proper repeatability, as well as low cost. Accordingly, nanostructured architectural sensing cues have received enormous attention toward versatile detection and sensing procedures. As a representational nanostructure, the MXene family has been widely introduced to tailor and augment sensor patterns by providing large surface area, tunable surface chemistry, superior electrical conductivity, chemical stability, compatibility with flexible substrates, and potential for multifunctionality. Additionally, they could be synthesized in various formations of film and layered designs, fibrous membranes, and gel-like structures, creating synergetic effects that can provide superior gas-sensing performance. Herein, the synthesis and benefits of MXene nanosheets as gas-sensitive materials, in tandem with the past-to-present progress of MXene-based gas sensors in the formation of films, fibrous, and gel-like configurations, are comprehensively reviewed. As an in-depth reference, the present overview could shed light on further advancing gas sensor architectures developed based on MXene structures.

Long-term mortality effects of particulate air pollution have been investigated in a causal analytic frame, while causal evidence for associations with gaseous air pollutants remains extensively lacking, especially for carbon monoxide (CO) and sulfur dioxide (SO2). In this study, we estimated the causal relationship of long-term exposure to nitrogen dioxide (NO2), CO, SO2, and ozone (O3) with mortality. Utilizing the data from National Morbidity, Mortality, and Air Pollution Study, we applied a variant of difference-in-differences (DID) method with conditional Poisson regression and generalized weighted quantile sum regression (gWQS) to investigate the independent and joint effects. Independent exposures to NO2, CO, and SO2 were causally associated with increased risks of total, nonaccidental, and cardiovascular mortality, while no evident associations with O3 were identified in the entire population. In gWQS analyses, an interquartile range-equivalent increase in mixture exposure was associated with a relative risk of 1.067 (95% confidence interval: 1.010-1.126) for total mortality, 1.067 (1.009-1.128) for nonaccidental mortality, and 1.125 (1.060-1.193) for cardiovascular mortality, where NO2 was identified as the most significant contributor to the overall effect. This nationwide DID analysis provided causal evidence for independent and combined effects of NO2, CO, SO2, and O3 on increased mortality risks among the US general population.

Ambient air pollutants exposures may lead to aggravated Metabolic Dysfunction-Associated Fatty Liver Disease (MAFLD). However, there is still a scarcity of empirical studies that have rigorously estimated this association, especially in regions where air pollution is severe. To fill in the literature gap, we conducted a cross-sectional study involving 2711,207 adults living in five regions of southern Xinjiang Uyghur Autonomous Region in 2021. Using a Space-Time Extra-Trees model, we assessed the four-year (2017-2020) average concentrations of particulate matter with aerodynamic diameter ≤1 µm (PM1), particulate matter with aerodynamic diameter ≤2.5 µm (PM2.5), particulate matter with aerodynamic diameter ≤10 µm (PM10), ozone (O3), sulfur dioxide (SO2), and carbon monoxide (CO), and then assigned these values to the participants. Generalized linear mixed models were employed to examine the relationships between air pollutants and the prevalence of MAFLD, with adjustment for multiple confounding factors. The odds ratios and 95% confidence intervals of MAFLD were 2.002 (1.826-2.195), 1.133 (1.108-1.157), 1.034 (1.027-1.040), 1.077 (1.023-1.134), 2.703 (2.322-3.146) and 1.033 (1.029-1.036) per 10 µg/m3 increase in the 4-year average PM1, PM2.5, PM10, O3, SO2 and CO exposures, respectively. The robustness of the findings was confirmed by a series of sensitivities. In summary, long-term exposure to ambient air pollutants was associated with increased odds of MAFLD, particularly in males and individuals with unhealthy lifestyles.

Some studies have shown the effect of air pollution on migraine. However, it needs to be confirmed in larger-scale studies, as scientific evidence is scarce regarding the association between air pollution and migraine. Therefore, this systematic review aims to determine whether there are associations between outdoor air pollution and migraine. A literature search was performed in Scopus, Medline (via PubMed), EMBASE, and Web of Science. A manual search for resources and related references was also conducted to complete the search. All observational studies investigating the association between ambient air pollution and migraine, with inclusion criteria, were entered into the review. Fourteen out of 1417 identified articles met the inclusion criteria and entered the study. Among the gaseous air pollutants, there was a correlation between exposure to nitrogen dioxide (NO2) (78.3% of detrimental relationships) and carbon monoxide (CO) (68.0% of detrimental relationships) and migraine, but no apparent correlation has been found for sulfur dioxide (SO2) (21.2% of detrimental relationships) and ozone (O3) (55.2% of detrimental relationships). In the case of particulate air pollutants, particulate matter with a diameter of 10 μm or less (PM10) (76.0% of detrimental relationships) and particulate matter with a diameter of 2.5 μm or less (PM2.5) (61.3% of detrimental relationships) had relationships with migraine. In conclusion, exposure to NO2, CO, PM10, and PM2.5 is associated with migraine headaches, while no conclusive evidence was found to confirm the correlation between O3 and SO2 with migraine. Further studies with precise methodology are recommended in different cities around the world for all pollutants with an emphasis on O3 and SO2.

The 2021 WHO guidelines stress the importance of measuring ultrafine particles using particle number concentration (PNC) for health assessments. However, commonly used particle metrics such as aerodynamic diameter and number concentrations do not fully capture the diverse chemical makeup of complex particles. To address this issue, our study used high-throughput mass spectrometry to analyze the properties of cooking oil fumes (COFs) in real time and evaluate their impact on BEAS-2B cell metabolism. Results showed insignificant differences in COF number size distributions between soybean oil and olive oil (peak concentrations of 5.20 × 105/cm3), as well as between corn oil and peanut oil (peak concentrations of 4.35 × 105/cm3). Despite the similar major chemical components among the four COFs, variations in metabolic damage were observed, indicating that the relatively small amount of chemical components of COFs can also influence particle behavior within the respiratory system, thereby impacting biological responses. Additionally, interactions between accompanying gaseous COFs and particles may alter their chemical composition through various mechanisms, introducing additional chemicals and modifying existing proportions. Hence, the chemical composition and gaseous components of COFs hold equal importance to the particle number concentration (PNC) when assessing their impact on human health. The absence of these considerations in the current guidelines underscores a research gap. It is imperative to acknowledge that for a more comprehensive approach to safeguarding public health, guidelines must be regularly updated to reflect new scientific findings and robust epidemiological evidence.

BACKGROUND: Ambient air pollution increases the risk of respiratory mortality and morbidity, but evidence concerning effects of air pollution on chronic bronchitis (CB) is scarce. This study aimed to evaluate the associations of a set of air pollutants with the burden of CB, and to explore potential modifiers on the associations.
METHODS: In 2020, a total of 6,556,440 adults living in the Northwestern region of China were recruited. The Space-Time Extra-Trees model was employed to assess the annual average concentrations of six air pollutants for the three years (2017-2019) before 2020 , and subsequently allocated to the participants based on the latitude and longitude of their home addresses. We investigated the associations between the levels of various air pollutants and the odds of CB using generalized linear mixed models, and conducted multiple sensitivity analyses and subgroup analyses.
RESULTS: The odds of CB displays an approximately linear association with particulate matter with aerodynamic diameter ≤2.5 μm (PM2.5), particulate matter with aerodynamic diameter ≤10 μm (PM10), while it shows a non-linear relationship with gaseous pollutants. In the adjusted model, the odds ratios and 95% confidence intervals for CB per 10 μg/m3 increase in PM2.5, PM10, and sulfur dioxide (SO2) were 1.297 (1.262-1.332), 1.072 (1.064-1.080), and 2.587 (2.186-3.063), respectively. Furthermore, several additional sensitivity analyses demonstrated the stability of these associations. Subgroup analyses found that the aforementioned associations were greater among participants aged below 50 years old and those who smoked and had no leisure time exercise.
CONCLUSIONS: Long-term exposure to ambient air pollutants may increase the odds of CB, especially among younger people and those with unhealthy lifestyles.

Exposure to air pollution has been linked to an increased risk of premature mortality. However, the acute effects of air pollution on the risk of non-accidental mortality have not been extensively researched in developing countries, and the findings thus far have been inconsistent. Therefore, this study aimed to examine the association between short-term exposure to six pollutants (PM2.5, PM10, SO2, NO2, O3, and CO) and non-accidental mortality in Beijing, China.
Daily data on non-accidental deaths were gathered from 1 January 2017 to 31 December 2018. Air pollution data for the same period were collected from 35 fixed-site air quality monitoring stations in Beijing. Generalized additive models (GAM) based on Poisson regression were used to investigate the association between non-accidental mortality in emergency department visits and the daily average levels of air pollutants.
There were 8,676 non-accidental deaths recorded during 2017-2018. After sensitivity analysis, short-term exposure to air pollutants, particularly gaseous pollutants, was linked to non-accidental mortality. Specifically, for every 10 μg/m3 increase (5 μg/m3 in SO2, 0.5 mg/m3 in CO) of SO2 (lag 04), NO2 (lag 04), O3 (lag 05), and CO (lag 04), the relative risk (RR) values were 1.054 (95% CI: 1.009, 1.100), 1.038 (95% CI: 1.013, 1.063), 1.032 (95% CI: 1.011, 1.054), and 1.034 (95% CI: 1.004, 1.066), respectively. In terms of causes of death, short-term exposure to NO2, SO2, and O3 increased the risk of circulatory mortality. Further stratified analysis revealed that the stronger associations were presented in females for O3 while in males for CO. People aged 65 and over were strongly associated with ambient air pollution.
Our study showed that ambient air pollutants were associated with non-accidental mortality. Our findings suggested that efforts to control gaseous pollution should be stepped up, and vulnerable groups should be the focus of health protection education.

Air pollution remains a major threat to cardiovascular health and most acute myocardial infarction (AMI) deaths occur at home. However, currently established knowledge on the deleterious effect of air pollution on AMI has been limited to routinely monitored air pollutants and overlooked the place of death. In this study, we examined the association between short-term residential exposure to China\'s routinely monitored and unmonitored air pollutants and the risk of AMI deaths at home. A time-stratified case-crossover analysis was undertaken to associate short-term residential exposure to air pollution with 0.1 million AMI deaths at home in Jiangsu Province (China) during 2016-2019. Individual-level residential exposure to five unmonitored and monitored air pollutants including PM1 (particulate matter with an aerodynamic diameter ≤ 1 μm) and PM2.5 (particulate matter with an aerodynamic diameter ≤ 2.5 μm), SO2 (sulfur dioxide), NO2 (nitrogen dioxide), and O3 (ozone) was estimated from satellite remote sensing and machine learning technique. We found that exposure to five air pollutants, even below the recently released stricter air quality standards of the World Health Organization (WHO), was all associated with increased odds of AMI deaths at home. The odds of AMI deaths increased by 20% (95% confidence interval: 8 to 33%), 22% (12 to 33%), 14% (2 to 27%), 13% (3 to 25%), and 7% (3 to 12%) for an interquartile range increase in PM1, PM2.5, SO2, NO2, and O3, respectively. A greater magnitude of association between NO2 or O3 and AMI deaths was observed in females and in the warm season. The greatest association between PM1 and AMI deaths was found in individuals aged ≤ 64 years. This study for the first time suggests that residential exposure to routinely monitored and unmonitored air pollutants, even below the newest WHO air quality standards, is still associated with higher odds of AMI deaths at home. Future studies are warranted to understand the biological mechanisms behind the triggering of AMI deaths by air pollution exposure, to develop intervention strategies to reduce AMI deaths triggered by air pollution exposure, and to evaluate the cost-effectiveness, accessibility, and sustainability of these intervention strategies.

OBJECTIVE: We aimed to evaluate the relationship between the composition of particulate matter (PM) and gestational diabetes mellitus (GDM) by a comprehensively review of epidemiological studies.
METHODS: We systematically identified cohort studies related to air pollution and GDM risk before February 8, 2023 from six databases (PubMed, Embase, Web of Science Core Collection, China National Knowledge Infrastructure, Wanfang Data Knowledge Service Platform and Chongqing VIP Chinese Science and Technology Periodical databases). We calculated the relative risk (RR) and its 95% confidence intervals (CIs) to assess the overall effect by using a random effects model.
RESULTS: This meta-analysis of 31 eligible cohort studies showed that exposure to PM2.5, PM10, SO2, and NO2 was associated with a significantly increased risk of GDM, especially in preconception and first trimester. Analysis of the components of PM2.5 found that the risk of GDM was strongly linked to black carbon (BC) and nitrates (NO3-). Specifically, BC exposure in the second trimester and NO3- exposure in the first trimester elevated the risk of GDM, with the RR of 1.128 (1.032-1.231) and 1.128 (1.032-1.231), respectively. The stratified analysis showed stronger correlations of GDM risk with higher levels of pollutants in Asia, except for PM2.5 and BC, which suggested that the specific composition of particulate pollutants had a greater effect on the exposure-outcome association than the concentration.
CONCLUSIONS: Our study found that ambient air pollutant is a critical factor for GDM and further studies on specific particulate matter components should be considered in the future.