Nitrogen Dioxide Research Articles

Association Between Long‑Term Exposure to Air Pollution and the Rate of Mortality After Hip Fracture Surgery in Patients Older Than 60 Years: Nationwide Cohort Study in Taiwan.

To enhance postoperative patient survival, particularly in older adults, understanding the predictors of mortality following hip fracture becomes paramount. Air pollution, a prominent global environmental issue, has been linked to heightened morbidity and mortality across a spectrum of diseases. Nevertheless, the precise impact of air pollution on hip fracture outcomes remains elusive. This retrospective study aims to comprehensively investigate the profound influence of a decade-long exposure to 12 diverse air pollutants on the risk of post-hip fracture mortality among older Taiwanese patients (older than 60 years). We hypothesized that enduring long-term exposure to air pollution would significantly elevate the 1-year mortality rate following hip fracture surgery. From Taiwan's National Health Insurance Research Database, we obtained the data of patients who underwent hip fracture surgery between July 1, 2003, and December 31, 2013. Using patients' insurance registration data, we estimated their cumulative exposure levels to sulfur dioxide (SO2), carbon dioxide (CO2), carbon monoxide (CO), ozone (O3), particulate matter having a size of <10 μm (PM10), particulate matter having a size of <2.5 μm (PM2.5), nitrogen oxides (NOX), nitrogen monoxide (NO), nitrogen dioxide (NO2), total hydrocarbons (THC), nonmethane hydrocarbons (NMHC), and methane (CH4). We quantified the dose-response relationship between these air pollutants and the risk of mortality by calculating hazard ratios associated with a 1 SD increase in exposure levels over a decade. Long-term exposure to SO2, CO, PM10, PM2.5, NOX, NO, NO2, THC, NMHC, and CH4 demonstrated significant associations with heightened all-cause mortality risk within 1 year post hip fracture surgery among older adults. For older adults, each 1 SD increment in the average exposure levels of SO2, CO, PM10, PM2.5, NOX, NO, NO2, THC, NMHC, and CH4 corresponded to a substantial escalation in mortality risk, with increments of 14%, 49%, 18%, 12%, 41%, 33%, 38%, 20%, 9%, and 26%, respectively. We further noted a 35% reduction in the hazard ratio for O3 exposure suggesting a potential protective effect, along with a trend of potentially protective effects of CO2. This comprehensive nationwide retrospective study, grounded in a population-based approach, demonstrated that long-term exposure to specific air pollutants significantly increased the risk of all-cause mortality within 1 year after hip fracture surgery in older Taiwanese adults. A reduction in the levels of SO2, CO, PM10, PM2.5, NOX, NO, NO2, THC, NMHC, and CH4 may reduce the risk of mortality after hip fracture surgery. This study provides robust evidence and highlights the substantial impact of air pollution on the outcomes of hip fractures.

Reconciling Modeled and Observed Δ17O(NO3−) in Beijing Winter Haze With Heterogeneous Chlorine Chemistry

AbstractThe fine particulate matter (PM2.5) in Chinese megacities has declined significantly after the implementation of strict mitigation strategies since 2013. However, the concentration of wintertime nitrate in PM2.5 (p‐NO3‐) has only changed slightly and became the dominant inorganic component despite considerable precursor emission reductions. Discerning chemical mechanisms leading to nitrate growth during haze events is critical to implementing effective pollution mitigation policies. The oxygen isotope anomaly of nitrate (Δ17O(NO3−)) is a powerful means to distinguish nitrate formation mechanisms. Nevertheless, the observed high Δ17O(NO3−) values were significantly underestimated by chemical transport models during extreme haze events (PM2.5 &gt; 225 μg m−3) in Beijing, indicating an incomplete understanding of nitrate chemistry. To reconcile this model‐observation discrepancy, we compiled reported Δ17O(NO3−) data in Beijing haze along with relevant observational parameters (e.g., hydroxyl (OH) reactivity, peroxyl radical concentrations), then tested assumptions on Δ17O of key precursors (e.g., OH and nitrogen dioxide (NO2)), recalculated Δ17O(NO3−) and compared them with observations. Our results indicate that considering heterogeneous dinitrogen pentoxide reactions on chlorine‐containing aerosols (N2O5 + Cl− chemistry) with a nitryl chloride (ClNO2) yield of ∼0.75 can explain the observed high Δ17O(NO3−) during extreme haze events. According to the Δ17O(NO3−) data, on average this heterogeneous N2O5 + Cl− chemistry can explain ∼60% of nighttime nitrate production and make daytime and nocturnal pathways equally important in winter Beijing haze (PM2.5 &gt; 75 μg m−3). Our results highlight the critical role of reactive chlorine chemistry in air pollution/chemistry in inland cities.

Recent Insights into the Environmental Determinants of Childhood Asthma.

Ubiquitous environmental exposures, including ambient air pollutants, are linked to the development and severity of childhood asthma. Advances in our understanding of these links have increasingly led to clinical interventions to reduce asthma morbidity. We review recent work untangling the complex relationship between air pollutants, including particulate matter, nitrogen dioxide, and ozone and asthma, such as vulnerable windows of pediatric exposure and their interaction with other factors influencing asthma development and severity. These have led to interventions to reduce air pollutant levels in children's homes and schools. We also highlight emerging environmental exposures increasingly associated with childhood asthma. Growing evidence supports the present threat of climate change to children with asthma. Environmental factors play a large role in the pathogenesis and persistence of pediatric asthma; in turn, this poses an opportunity to intervene to change the course of disease early in life.

Evaluating the performance of carbon-based adsorbents fabricated from renewable biomass precursors for post-combustion CO2 capture

The significant increase in atmospheric CO2 concentration originated mainly from fossil fuels combustion has encouraged the development and improvement of CO2 separation operations to reduce emissions and control climate change and global warming. Therefore, this work is focused on the separation of CO2 from N2 in flue gas streams under post-combustion conditions by developing low-cost adsorbents. Six carbons were fabricated from biomass resources (olive stones and almond shells) to assess their influence on CO2 adsorption capacity: One carbonized and two KOH-activated carbons with carbon/KOH ratio of 1:2 and 1:4 (w/w) for each precursor. The carbons were characterized by field emission scanning electron microscopy (FESEM), transmission electron microscopy (TEM), elemental analysis, nitrogen and carbon dioxide adsorption–desorption analysis, X-ray diffraction (XRD), Fourier transform infrared (FTIR), X-ray photoelectron spectroscopy (XPS) and point of zero charge determination. In addition, the equilibrium adsorption data of pure components for all adsorbents were measured at 0, 25 and 50 °C between 0 and 760 mmHg and CO2/N2 selectivity was determined. Activated carbons were found to have higher CO2 adsorption capacity but with a reduction in apparent selectivity. Dynamic binary adsorption simulations performed in a fixed-bed column demonstrated that the activated carbon produced from olive stones with a carbon/KOH ratio of 1:4 (w/w) can separate a mixture of 14 % CO2 and 86 % N2 at 25 and 50 °C with the highest selectivity, CO2 adsorption capacity, CO2 purity and N2 recovery factor. Reducing flow rate, the breakthrough time increased. Moreover, the breakthrough time was reduced by increasing the temperature from 25 to 50 °C owing to the exothermic nature of adsorption process.

Risk of dementia due to Co-exposure to air pollution and neighborhood disadvantage

BackgroundCo-exposure to air pollution and neighborhood disadvantage may influence cognition decline. We tested these associations in the context of dementia risk. MethodsWe leveraged a cohort of adults ≥65 years (n = 5397) enrolled from 2011 to 2018 in the National Health and Aging Trends Study (NHATS). Particulate matter (PM) ≤ 10 μm in diameter, PM ≤ 2.5 μm in diameter, carbon monoxide, nitric oxide, and nitrogen dioxide - and neighborhood disadvantage were tested for joint associations with dementia risk. Pollutant concentrations at the 2010 census tract level were assigned using the US Environmental Protection Agency's Community Multiscale Air Quality Modeling System. Neighborhood disadvantage was defined using the tract Social Deprivation Index (SDI). Dementia was determined through self- or proxy-report or scores indicative of “probable dementia” according to NHATS screening tools. Joint effects of air pollutants and SDI were tested using quantile g-computation Cox proportional hazards models. We also stratified joint air pollution effects across SDI tertiles. Analyses adjusted for age at enrollment, sex, education, partner status, urbanicity, income, race and ethnicity, years at residence, census segregation, and census region. ResultsSDI score (aHR = 1.08; 95% CI 0.96, 1.22), joint air pollution (aHR = 1.03, 95% CI 0.92, 1.16) and joint SDI with air pollution (aHR = 1.04, 95% CI 0.89, 1.22) were not associated with dementia risk. After accounting for competing risk of death, joint SDI with air pollution was not associated with dementia risk (aHR = 1.06; 95% CI 0.87, 1.29). In stratified models, joint air pollution was associated with greater risk of dementia at high (aHR = 1.19; 95% CI 0.87, 1.63), but not at medium or low SDI. ConclusionAir pollution was associated with greater dementia risk in disadvantaged areas after accounting for competing risks. Air pollution associations with dementia incidence may be attenuated when other risk factors are more prominent in disadvantaged neighborhoods.

Environmental and health impacts of air pollution: A mini-review

Air pollution is one of the leading risk factors for death but also a significant contributor to the global disease burden, affecting quality of life. According to a World Health Organisation (WHO) report, seven million people die from air pollution every year, and 9 out of 10 people worldwide breathe polluted air. Any person can be affected by exposure to polluted air, especially the elderly, children, pregnant women, and people with comorbidities. Some studies indicate that the diseases most affected by air pollution are respiratory infections, chronic obstructive pulmonary disease (COPD), lung cancer, and cardiovascular diseases. The degree of effect on the body depends on the pollutant composition, source and dose, level and duration of exposure to polluted air. Particulate matter (PM10 and PM2.5), carbon monoxide (CO), ozone (O3), nitrogen dioxide (NO2), and sulphur dioxide (SO2) could lead to air pollution. Long-term exposure to air pollution can affect every organ in the body and worsen existing health conditions. Short-term exposure to contaminants can include unpleasant sensations such as coughing, wheezing, shortness of breath, eye, nose, and throat irritation, headache, dizziness, and fatigue. Community and individual solutions such as using clean fuel, wearing personal masks, filtering indoor air, and ventilating need to be taken to reduce the impact of air pollution.

High-Resolution Nitrogen Dioxide Measurements from an Airborne Fiber Imaging Spectrometer over Tangshan, China

The pollution caused by nitrogen dioxide is a major environmental problem in China. This study introduces a new type of atmospheric trace gas remote-sensing instrument, an airborne fiber imaging spectrometer. This spectrometer has a spectral range of 300–410 nm and works in push-broom mode with a 30° field of view on a flight path. Flight experiments were conducted on 30 December 2022 and 5 January 2023, covering heavily polluted areas east of Beijing and Tangshan. This equipment obtained the density distribution of NO2 over the flight area. The results showed that pollution was mainly concentrated in the Caofeidian area and at the power station in the north, and the main source of pollution was anthropogenic. Satellite and airborne data near the pollution points were compared, and the two datasets showed a positive correlation with a correlation coefficient of 0.78 and 0.7, on the two days, respectively. This study demonstrates the capability of an airborne fiber imaging spectrometer for NO2 regional emission remote sensing and identifying the pollution points.

RPCA-based techniques for pattern extraction, hotspot identification and signal correction using data from a dense network of low-cost NO2 sensors in London

High-density low-cost air quality sensor networks are a promising technology to monitor air quality at high temporal and spatial resolution. However the collected data is high-dimensional and it is not always clear how to best leverage this information, particularly given the lower data quality coming from the sensors. Here we report on the use of robust Principal Component Analysis (RPCA) using nitrogen dioxide data obtained from a recently deployed dense network of 225 air pollution monitoring nodes based on low-cost sensors in the Borough of Camden in London. RPCA addresses the brittleness of singular value decomposition towards outliers by using a decomposition of the data into low-rank and sparse contributions, with the latter containing outliers. The modal decomposition enabled by RPCA identifies major periodic patterns including spatial and temporal bias, dominant spatial variance, and north-south bias. The five most descriptive components capture 98 % of the data's variance, achieving a compression by a factor of 1500. We present a new technique that uses the sparse part of the data to identify hotspots. The data indicates that at the locations of the top 15 % most susceptible nodes in the network, the model identifies 23 % more hotspots than in all other locations combined. Moreover, the median hotspot event at these at-risk locations exceeds the mean NO2concentration by 33μg/m3. We show the potential of RPCA for signal correction; it corrects random errors yielding a reference signal with R2>0.8. Moreover, RPCA successfully reconstructs missing data from a sensor with R2=0.72 from the rest of the sensor network, an improvement upon PCA of around 50 %, allowing air quality estimations even if a sensor is out of use temporarily.

Air pollution, APOE genotype and risk of dementia among individuals with cardiovascular diseases: A population-based longitudinal study

Individuals with cardiovascular disease (CVD) are particularly vulnerable to dementia, but it remains unclear whether air pollution exposure links with higher risk of dementia among those with CVD. The data were derived from the UK Biobank study (UKB). Dementia-free participants with CVD at baseline were included. Air pollution exposure was assessed through land use regression models, including particulate matter (PM2.5, PM2.5-10, and PM10), nitrogen dioxide (NO2), and nitrogen oxides (NOX). A Cox proportional hazards model was used to investigate the associations between air pollution exposure and incident dementia among individuals with CVD. Air pollution was associated with dementia among individuals with CVD, and the hazard ratios of dementia associated with each interquartile range (IQR) μg/m3 increase in air pollution were 1.07 (95% CI: 1.02, 1.12) for PM2.5, 1.10 (95% CI: 1.04, 1.15) for PM10, 1.08 (95% CI: 1.03, 1.14) for NO2 and 1.05 (95% CI: 1.00, 1.09) for NOx. Associations between air pollution and all-cause dementia were found to be significant among individuals with hypertension. Adverse effects of air pollution were also observed for Alzheimer's dementia (AD) and vascular dementia (VaD), with a higher effect for AD. Observed associations remained similar in subgroups of APOE ε4 carriers and noncarriers, although there was a higher risk difference across different air pollution concentration among these individuals carrying APOE ε4. Air pollution emerges as a critical risk factor for dementia among individuals with CVD, regardless of genetic susceptibility indicated by the APOE genotype. Notably, individuals with hypertension might be susceptible to the adverse effects of air pollution, leading to a higher incidence of dementia. Understanding these impacts on dementia among individuals with CVD may promote better targeted prevention and clinical management strategies.

Deep Learning for Gas Sensing via Infrared Spectroscopy.

Deep learning methods, a powerful form of artificial intelligence, have been applied in a number of spectroscopy and gas sensing applications. However, the speciation of multi-component gas mixtures from infrared (IR) absorption spectra using deep learning remains to be explored. Here, we propose a one-dimensional deep convolutional neural network gas classification model for the identification of small molecules of interest based on IR absorption spectra in flexible user-defined frequency ranges. The molecules considered include ten that are of interest in the atmosphere or in industrial and environmental processes: water vapor, carbon dioxide, ozone, nitrous oxide, carbon monoxide, methane, nitric oxide, sulfur dioxide, nitrogen dioxide, and ammonia. A simulated dataset of IR absorption spectra for mixtures of these molecules diluted in air was generated and used to train a deep learning model. The model was tested against simulated spectra containing noise and was found to provide speciation predictions with accuracy from 82 to 97%. The internal operation of the model was investigated using class activation maps that illustrate how the model prioritizes spectral information for classification. Finally, the model was demonstrated for the prediction of speciation for two synthetic experimental mixture spectra. The proposed model and the dataset generation strategies are generalized and can be implemented for other gases, different frequency ranges, and spectroscopy types. The multi-component speciation method developed herein is the first application of a convolutional neural network model, trained on HITRAN-based simulations, for spectral identification.

Association between NO2 and human mobility: a two-year spatiotemporal study during the COVID-19 pandemic in Southeast Asia

ABSTRACT In the wake of the COVID-19 pandemic, global efforts to mitigate the spread of the virus have led to widespread lockdowns and movement restrictions. Earlier studies have reported a notable positive correlation between nitrogen dioxide (NO2) levels and mobility during the initial 2020 lockdowns. However, our explorative investigation in Southeast Asia observed that, despite their similar spatial distribution, NO2 does not consistently align with mobility patterns. This observation indicates the existence of additional influential factors apart from mobility contributing to NO2 variation, necessitating a more comprehensive examination. Subsequently, we developed a trained Multi-Layer Perceptron (MLP) model and leveraged SHapley Additive exPlanations (SHAP) values. Our analysis extends beyond mobility to encompass diverse potential factors such as travel modes and meteorological factors. The model results suggest that, while as expected mobility has a strong impact on NO2 column density, a more accurate prediction requires considering different travel modes (i.e. driving and walking). Furthermore, the study reveals that spatio-temporal heterogeneity and meteorological factors also play roles in shaping NO2 level. These findings emphasize the importance of integrating such multifaceted considerations in future NO2 study for a more accurate and holistic understanding.

Time-series analysis of the association between air pollution exposure and outpatient visits for dry eye disease: a case study in Zhengzhou, China.

Dry eye disease (DED) is a prevalent ocular surface disease that significantly impacts patients' quality of life. The association between air pollution and the risk of dry eye disease remains uncertain. Data on outdoor air pollutants, meteorological information, and outpatient visits for DED were collected from July 1, 2014, to December 31, 2019. The relationship between ambient air pollutants and DED outpatient visits was analyzed using a generalized additive model with a Poisson distribution. Among the 5,204 DED patients included in the study, 63.76% were female and 36.24% were male. The single-pollutant model revealed a significant association between a 10 μg/m3 increase in concentrations of fine-particulate matter with a median aerometric diameter of less than 10 μm (PM10), sulfur dioxide (SO2), nitrogen dioxide (NO2), and carbon monoxide (CO) and outpatient visits for DED. Fine-particulate matter with a median aerometric diameter of less than 2.5 μm (PM2.5) showed a significant association with DED outpatient visits in males and the 19-59 years age group. The strongest associations between air pollutants and outpatient visits were observed in male patients and during the cold season. The noteworthy correlation between air pollutants and DED outpatient visits can offer evidence for policy makers and underscore the significance of reinforcing environmental protection.

Investigating the spatiotemporal associations between meteorological conditions and air pollution in the federal state Baden-Württemberg (Germany)

When analyzing health data in relation to environmental stressors, it is crucial to identify which variables to include in the statistical model to exclude dependencies among the variables. Four meteorological parameters: temperature, ultraviolet radiation, precipitation, and vapor pressure and four outdoor air pollution parameters: ozone (O3\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ ext{O}_3$$\\end{document}), nitrogen dioxide (NO2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ ext{NO}_2$$\\end{document}), particulate matter (PM2.5\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$PM_{2.5}$$\\end{document}, PM10\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$PM_{10}$$\\end{document}) were studied on a daily basis for Baden-Württemberg (Germany). This federal state covers urban and rural compartments including mountainous and river areas. A temporal and spatial analysis of the internal relationships was performed among the variables using (a) cross-correlations, both on the grand ensemble of data as well as within subsets, and (b) the Local Indications of Spatial Association (LISA) method. Meteorological and air pollution variables were strongly correlated within and among themselves in time and space. We found a strong interaction between nitrogen dioxide and ozone, with correlation coefficients varying over time. The coefficients ranged from negative correlations in January (−0.84), April (−0.47), and October (−0.54) to a positive correlation in July (0.45). The cross-correlation plot showed a noticeable change in the correlation direction for O3\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ ext{O}_3$$\\end{document} and NO2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ ext{NO}_2$$\\end{document}. Spatially, NO2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ ext{NO}_2$$\\end{document}, PM2.5\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$PM_{2.5}$$\\end{document}, and PM10\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$PM_{10}$$\\end{document} concentrations were significantly higher in urban than rural regions. For O3\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ ext{O}_3$$\\end{document}, this effect was reversed. A LISA analysis confirmed distinct hot and cold spots of environmental stressors. This work examined and quantified the spatio-temporal relationship between air pollution and meteorological conditions and recommended which variables to prioritize for future health impact analyses. The results found are in line with the underlying physico-chemical atmospheric processes. It also identified postal code areas with dominant environmental stressors for further studies.

City-scale methane emissions from the midstream oil and gas industry: A satellite survey of the Zhoushan archipelago

As the second most abundant greenhouse gas after carbon dioxide, methane (CH4) leakage and emissions pose potential climate threats and environmental problems in the midstream oil and gas storage and transportation (OGST) industry. In this study, the Tropospheric Monitoring Instrument on the Sentinel-5P satellite was adopted to investigate the coverage of atmospheric CH4 concentrations over the Zhoushan archipelago, which is China's largest OGST base. Specifically, the distribution of atmospheric CH4 and nitrogen dioxide (NO2) concentrations over Zhoushan in August 2022 and August 2023 were evaluated, where changes in concentrations around the OGST companies were monitored. Using surface temperature inversion and average temperature statistics, we analyzed the heat island effect in Zhoushan. The results showed that: (1) although there is limited valid data (>200 pixel/day) for Zhoushan, the amount of valid data increased from 3.2% in January 2020 to 32.3% in August 2023; (2) around the region of the OGST companies, the atmospheric CH4 concentration shown significant variation at both the spatial and temporal scales, which may be due to the storage, loading, and unloading of petroleum products; (3) under geographic isolation conditions, NO2 can be used as a tracer gas to track the CH4 emissions from OGST companies; and (4) Surface temperature analysis underscores OGST companies' contribution to Zhoushan's urban heat island effect, with local average temperature increases outstripping broader national trends, highlighting the intricate interplay of human and natural factors in the city-scale climate dynamics.

Association of Long-Term Exposure to Ambient Air Pollution With the Risk of Acute Primary Angle Closure.

The purpose of this study was to investigate the association between long-term exposure to ambient air pollutants and the risk of acute primary angle closure (APAC). Two hundred eighty-one (281) patients with APAC and 730 age- and sex-matched controls hospitalized between January 2017 and December 2019 were enrolled in this retrospective case-control study. Residential exposure to ambient air pollutants, including fine particulate matter (PM2.5), inhalable particulate (PM10), nitrogen dioxide (NO2), sulfur dioxide (SO2), and ozone were estimated by satellite-models or ground measurement. Multivariate regression analyses explored the association between annual air pollutants exposure and the risk of APAC. Of the 1011 participants (31.1% were male subjects), the average age was 64.0years. Long-term exposure to PM2.5, PM10, and SO2 were significantly associated with an increased risk of APAC. The adjusted odds ratios (aORs) for each interquartile range (IQR) increment of PM2.5, PM10, and SO2 were 1.28 (95% confidence interval [CI] = 1.06-1.57), 1.26 (95% CI = 1.06-1.50), and 1.30 (95% CI = 1.04-1.62) separately, after controlling for confounders. Robust associations were observed for a longer lag 2-year exposure. Long-term exposure to PM2.5, PM10, and SO2 was associated with an increased risk of APAC in a Chinese population. Our findings provide epidemiological implications on the adverse effects of air pollution on ocular diseases. Long-term exposure to ambient air pollutants increased the risk of APAC.

Hydrazine and its Derivatives: Role on Nitrogen Dioxide Hydrolysis and Ensuing Nucleation in the Atmosphere

AbstractHydrazine (HD) and mono‐methyl hydrazine (MMH), as the compositions of rocket fuels and corrosion inhibitor, have a significant impact on the atmospheric environment. The effects of them on the reaction between NO2 and H2O were investigated theoretically from mechanism and kinetics, and it is expected that they can promote the hydrolysis of NO2 due to their lower free energy barriers. For the subsequent reaction HNO3+HONO+HD/MMH, acid base complex and zwitterionic structure were produced through isomerization. When one or two water molecules were involved in the subsequent reaction, only zwitterionic structure can be found with the lower free energy barrier, and the products were more stable than those without water molecules. To study the atmospheric behavior of HD/MMH, the structures, thermodynamics, interaction forces and temperature dependence of the clusters, which were consisted with HNO3 and HONO with the base molecules including ammonia, amine and amide, were further calculated, and the results show that the hydrogen bond is the main interaction in the clusters. The global minima remained fixed when the temperature increases from 200 K to 325 K. The forming reactions of the clusters were spontaneous, suggesting that ammonia, amine and amide can promote the nucleation of HNO3 and HONO molecules.

Microelectrode‐enabled Electrocrystallization of Cobalt TCNQ Complex for Gas Sensing

AbstractElectrocrystallization is a promising method for controlled charge‐transfer complex (CTC) deposition on microfabricated electrodes for gas sensing applications. However, there remains a gap in our understanding of CTC electrodeposition. In this study, we focus on investigating the electrocrystallization of cobalt tetracyanoquinodimethane (Co‐TCNQ) on a microdisk electrode to elucidate and control the process. Leveraging the microelectrode technique, we conduct steady‐state measurements to observe nucleation and crystal growth dynamics, particularly in the early stages of electrocrystallization. We use cyclic voltammetry and chronoamperometry to examine Co‐TCNQ electrocrystallization under various electrolytic conditions. We identify electrocrystallization kinetics, ranging from electrokinetic to diffusion‐limited growth, governing the nucleation and growth of Co‐TCNQ crystals. Notably, we pinpoint the applied overpotential and precursor concentration range necessary for a single nucleation site on the microelectrode. Moreover, we demonstrate control over crystal orientation and morphology. Our findings reveal a nonclassical growth pathway for Co‐TCNQ crystals characterized by oriented attachment of small crystallites along the conductive long axis. Importantly, electrodeposited Co‐TCNQ on patterned microelectrodes exhibits selective sensing capabilities for nitrogen dioxide gas. Overall, this study sheds light on CTC electrodeposition through a proof‐of‐concept demonstration involving Co‐TCNQ electrodeposition on microelectrodes, presenting potential applications across diverse materials.

Strategies of realizing NO2 detections with enhanced selectivity and anti-humidity based on snowflake-like in-situ grown ZIF-8/ZnOHF composites

Realizing nitrogen dioxide (NO2) detections based on semiconductor-based gas sensors with high tolerance to humidity conditions is deemed to be a long-term challenge. To independently acknowledge the physiosorbed-water influence mechanism on semiconductor-based sensors, hydrophobic zeolitic imidazolate framework-8 (ZIF-8) covered chemisorbed-oxygen-nonexistence zinc hydroxyfluoride (ZnOHF) snowflake-like nanorod bundles are synthesized for NO2 detections with non-hindrance of interfering gases and high humidity in our work. Gas-sensing testing results display that the 0.6ZIF-8/ZnOHF-based gas sensor provides an optimum NO2 response of 12.1–10 ppm NO2 at the operating temperature of 200 ℃ with excellent NO2 selectivity. As the relative humidity (RH) increases from 20% RH to 80% RH, the response of the 0.6ZIF-8/ZnOHF sensor shows a marginal fluctuation of only 13%, exhibiting outstanding anti-humidity characteristics towards NO2 detections, the outperformed NO2 selectivity and humidity tolerance of which are greatly attributed to the unique band structures of ZnOHF and the surficial hydrophobic treatment by ZIF-8, which is further validated via In-situ diffuse reflection infrared Fourier transform spectroscopy (In-situ DRIFTS) and electronic structure analyses. Humidity impact on ZnOHF poses a persuasive evidence for establishing the separate physiosorbed water interfering mechanism on semiconductors. This work endows a perspective on optimizing humidity tolerance for semiconductor-based sensors at low operating temperature.

Ambient Air Pollution and Vision Disorder: A Systematic Review and Meta-Analysis.

The effects of air pollution on physical health are well recognized, with many studies revealing air pollution's effects on vision disorder, yet no relationship has been established. Therefore, a meta-analysis was carried out in this study to investigate the connection between vision disorder and ambient particles (diameter ≤ 2.5 µm (PM2.5), diameter ≤ 10 µm (PM10)) and gaseous pollutants (nitrogen dioxide (NO2), sulfur dioxide (SO2), carbon monoxide (CO), Ozone (O3)). Twelve relevant studies published by 26 February 2024 were identified in three databases. A pooled odds ratios (ORs) of 95% confidence intervals (CIs) were obtained using random-effects meta-analysis models. Meta-analysis results revealed that for every 10 µg/m3 increase in PM2.5 and NO2 exposure, a substantially higher incidence of vision disorder was observed (OR = 1.10; 95% CI: 1.01, 1.19; OR = 1.08, 95% CI: 1.00, 1.16). No significant correlation existed between exposure to PM10, SO2 and CO and vision disorder. However, O3 exposure was negatively associated with vision disorder. In addition, subgroup analyses revealed that PM2.5 exposure was significantly correlated with the risk of glaucoma and age-related macular degeneration and that children and adolescents were more susceptible to NO2 and PM2.5 than adults. Overall, exposure to air pollutants, especially PM2.5 and NO2, may increase the incidence of vision disorder.

Multiphase reactions of proteins in the air: Oligomerization, nitration and degradation of bovine serum albumin upon ambient exposure

Proteins in atmospheric aerosol can react with atmospheric pollutants such as ozone (O3) and nitrogen dioxide (NO2) in the atmosphere via the reactions of oxidation, nitration, and cross-linking etc. Currently, the reactions have been more thoroughly studied in the laboratory but rarely investigated in the ambient environment. In this study, we used bovine serum albumin (BSA) as the model protein to conduct the exposure experiment in the ambient environment in southern China, an area with increasing oxidative capacity, to investigate the reactions of proteins in the atmosphere. We observed the occurrence of oligomerization, nitration and degradation of BSA upon exposure. The mass fraction of BSA monomer decreased by 5.86 ± 1.61% after exposure and those of dimers, trimers and higher oligomers increased by 1.04 ± 0.49%, 1.37 ± 0.74% and 3.40 ± 1.06%, respectively. Simultaneously, the nitration degrees of monomers, dimers, trimers and higher oligomers increased by 0.42 ± 0.15%, 0.53 ± 0.15%, 0.55 ± 0.28% and 2.15 ± 1.01%, respectively. The results show that oligomerization was significantly affected by O3 and temperature and nitration was jointly affected by O3, temperature and relative humidity, indicating the important role of atmospheric oxidants in the atmospheric reactions of protein. Atmospheric degradation of BSA was observed with the release of free amino acids (FAAs) such as glycine, alanine, serine and methionine. Glycine was the dominant FAA with a molar yield ranging from ∼8% to 33% for BSA. The estimated stoichiometric coefficient (α) of glycine is 10−7–10−6 for the degradation of BSA upon O3. Our observation suggests the occurrence of protein reactions in the oxidative ambient environment, leading to the production of nitrated products, oligomers and low molecular weight products such as peptides and FAAs. This study may deepen the current understanding of the atmospheric reaction mechanisms and reveal the influence of environmental factors in the atmosphere.