Μm In Aerodynamic Diameter Research Articles

Age and sex differences in the effects of short- and long-term exposure to air pollution on endothelial dysfunction

Abstract Background Endothelial dysfunction is an integrated index of risk factor burden and a marker of atherosclerotic cardiovascular disease. Air pollution is widely acknowledged as a significant non-traditional risk factor for cardiovascular disease. However, the impact of air pollutants at varying concentrations and exposure durations on endothelial function in different populations remains unclear. Purpose We aimed to use brachial artery flow-mediated dilatation (FMD) to identify demographic differences in the effects of short- and long-term exposure to air pollution on endothelial dysfunction. Methods We measured FMD in 850 participants from October 2016 to January 2020. Location-specific concentrations of fine particulate matter <2.5 μm aerodynamic diameter (PM2.5), inhalable particulate matter <10 μm aerodynamic diameter (PM10), sulfur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (CO), and ozone (O3) measured by fixed ambient air monitoring stations were collected for short- and long-term exposure assessment. We used the moving average 7- and 14-day exposures before the date of FMD measurements to estimate the short-term exposure effects and the moving average 12-month exposures before the date of FMD measurements to estimate the long-term exposure effects. Multiple linear regression models and restricted cubic splines were used to assess the associations before and after stratified by age and sex. Results This study eventually included 828 participants [551 (66.5%) younger than 65 years and 553 (66.8%) men]. Each 10 μg/m³ increase in 12-month exposure to PM10 and NO2 was significantly and linearly associated with -0.20% (95% CI: -0.37 to -0.03) and -0.58% (95% CI: -0.99 to -0.18) changes in FMD in all participants. 12-month exposure to gaseous pollutants was also significantly but nonlinearly associated with lower FMD. 7-day exposure to Quartile 4 of SO2 was significantly associated with a 0.70% decrease in FMD compared to Quartile 1 (β = -0.70, 95% CI: -1.40 to -0.008). No relationships were observed between 7- and 14-day exposure to PM2.5, PM10, NO2, CO, and endothelial dysfunction. Although interaction effects were limited to SO2 and sex, significant associations with different air pollutants were only found in men and those younger than 65 years after stratified. Conclusions Long-term exposure to air pollution is strongly associated with decreased endothelial function, and susceptibility to air pollution varies significantly with age and sex. Further identification of different susceptible populations and proactive measures to mitigate air pollution may be beneficial in reducing the burden of cardiovascular disease.

Assessment of Multiple Planetary Boundary Layer Height Retrieval Methods and Their Impact on PM2.5 and Its Chemical Compositions throughout a Year in Nanjing

In this study, we investigate the planetary boundary layer height (PBLH) using micro-pulse lidar (MPL) and microwave radiometer (MWR) methods, examining its relationship with the mass concentration of particles less than 2.5 µm in aerodynamic diameter (PM2.5) and its chemical compositions. Long-term PBLH retrieval results are presented derived from the MPL and the MWR, including its seasonal and diurnal variations, showing a superior performance regarding the MPL in terms of reliability and consistency with PM2.5. Also examined are the relationships between the two types of PBLHs and PM2.5. Unlike the PBLH derived from the MPL, the PBLH derived from the MWR does not have a negative correlation under severe pollution conditions. Furthermore, this study explores the effects of the PBLH on different aerosol chemical compositions, with the most pronounced impact observed on primary aerosols and relatively minimal influence on secondary aerosols, especially secondary organics during spring. This study underscores disparities in PBLH retrievals by different instruments during long-term observations and unveils distinct relationships between the PBLH and aerosol chemical compositions. Moreover, it highlights the greater influence of the PBLH on primary pollutants, laying the groundwork for future research in this field.

Long-term exposure to NO2 and PM2.5 and the occurrence of chronic kidney disease among patients with type 2 diabetes in Taiwan

BackgroundIndividuals diagnosed with type 2 diabetes (T2D) frequently exhibit chronic kidney disease (CKD) which may be caused by environmental hazards such as exposure to air pollutants. However, limited research has explored the effects of prolonged exposure to air pollutants on CKD development in this population. This study examines the relationship between long-term exposure to air pollutants and CKD incidence in a longitudinal cohort of individuals with type 2 diabetes in Taiwan MethodsBetween 2003 and 2005, we recruited 1316 T2D patients (693 females [52.66 %]; mean age 56.16 ± 8.97 years). Patients were followed until December 31, 2012, with at least two clinical visits. Baseline demographics, medical history, and biomarker levels were collected. The development of CKD was determined by eGFR level < 60 mL/min/1.73 m2. Monthly averages of nitrogen dioxide (NO2) and fine particulate matter [PM ≤ 2.5 μm in aerodynamic diameter (PM2.5)] were acquired from 72 ambient air monitoring stations. The kriging method was employed to estimate the exposure levels to PM2.5, NO2, temperature, and relative humidity in the participants' residential areas. Cox regression with time-dependent covariates regression was applied to assess the impact of long-term exposure to air pollutants and CKD risk. ResultsOf 992 patients with normal renal function at baseline, 411 (41.43 %) experienced CKD occurrence over a median follow-up period of 5.45 years. The incidence of CKD was 93.96 cases per 1000 person-years. In multivariable adjusted models, patients exposed to PM2.5 levels above the third quartile of (>33.44 μg/m3) and NO2 levels above the fourth quartile (>22.55 ppb) were found to have an increased risk of CKD occurrence compared to lower exposure levels. ConclusionsThis longitudinal study highlights the increased risk of CKD in individuals with type 2 diabetes due to prolonged exposure to NO2 and PM2.5, emphasizing the need for tailored air quality management strategies for this high-risk population.

Assessing the oxidative potential of dust from great salt Lake

Great Salt Lake (GSL) is one of the world's largest inland bodies of saltwater. Climate change, drought, and water diversions have led to the GSL reaching historically low levels, exposing over 1945 km2 of lakebed. Dust events can transport particulate matter (PM) from the GSL's exposed lakebed to the adjacent urban areas, presenting air quality and health concerns. In this study, we assessed the oxidative potential (OP) of dust from the exposed GSL bed compared to dust samples collected from other regional playas and to reference Arizona test dust. The oxidative potential of PM10 (particles ≤10 μm in aerodynamic diameter) derived from these dusts was assessed by two acellular assays: the ascorbic acid (OPAA) and dithiothreitol (OPDTT) and two extraction solvents: phosphate buffer saline and Gamble's simulated lung fluid. All samples were also analyzed for elemental composition. Our results show that the concentration of As and Li in most of the GSL dust samples exceeded the Environmental Protection Agency (EPA) soil residential regional screening levels, and the OPAA and OPDTT of dust samples from GSL playas were generally higher than the OP of other regional playas. Our findings also indicated that the OP of the GSL dust was associated with metals, including Cu, Mn, Fe, and Al. This is the first study evaluating the oxidative potential of dust from the GSL, which improves our understanding of how increasing aridity, particularly desiccation of saline lakes, affects air quality and public health.

Association between exposure to air pollution and arterial stiffness in participants with and without atherosclerotic cardiovascular disease.

To assess the association of air pollution exposure at different time scales with arterial stiffness in participants with and without atherosclerotic cardiovascular disease (ASCVD). We measured participants' arterial stiffness with brachial-ankle pulse wave velocity (baPWV) from October 2016 to January 2020. Concentrations of air pollutants including fine particles < 2.5μm aerodynamic diameter (PM2.5), inhalable particles < 10μm aerodynamic diameter (PM10), sulfur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (CO), and ozone (O3) measured by fixed ambient air monitoring stations were collected for short- (7-day) and long-term (365-day) exposure assessment. We used generalized estimating equations (GEEs) to analyze and further explored the modification effects between ASCVD and air pollutants. Seven hundred sixty-five participants were finally included and four hunderd sixty (60.1%) participants had a history of ASCVD. Based on the partial regression coefficients (β) and 95% confidence intervals (95% CI) calculated from GEEs using linear regression, each 10μg/m3 increase in long-term exposure to PM2.5 and PM10 was associated with 31.85cm/s (95% CI, 17.97 to 45.73) and 35.93cm/s (95% CI, 21.01to50.84) increase in baPWV. There was no association between short-term exposure to air pollution and arterial stiffness. Although no significant interaction effect was observed between air pollution and ASCVD, baPWV showed a greater increment in the subgroup without ASCVD. Long-term exposure to air pollution is closely associated with higher arterial stiffness in participants with and without ASCVD. Reducing air pollution exposure is essential in the primary and secondary prevention of ASCVD.

Associations between indoor fine particulate matter (PM2.5) and sleep-disordered breathing in an urban sample of school-aged children

ObjectivesEnvironmental risk factors may contribute to sleep-disordered breathing. We investigated the association between indoor particulate matter ≤2.5µm in aerodynamic diameter (PM2.5) and sleep-disordered breathing in children in an urban US community. MethodsThe sample consisted of children aged 6-12years living in predominantly low-income neighborhoods in Boston, Massachusetts. Indoor PM2.5 was measured in participants’ main living areas for 7days using the Environmental Multipollutant Monitoring Assembly device. High indoor PM2.5 exposure was defined as greater than the sample weekly average 80th percentile level (≥15.6 μg/m3). Sleep-disordered breathing was defined as an Apnea-Hypopnea-Index (AHI) or Oxygen-Desaturation-Index (ODI) (≥3% desaturation) of ≥5 events/hour. Habitual loud snoring was defined as caregiver-report of loud snoring (most or all the time each week) over the past 4weeks. We examined the associations of PM2.5 with sleep-disordered breathing or snoring using logistic regression adjusting for potential confounders. ResultsThe sample included 260 children (mean age 9.6years; 41% female), with 32% (n = 76) classified as having sleep-disordered breathing. In a logistic regression model adjusted for socioeconomics and seasonality, children exposed to high indoor PM2.5 levels (n = 53) had a 3.53-fold increased odds for sleep-disordered breathing (95%CI: 1.57, 8.11, p = .002) compared to those with lower indoor PM2.5. This association persisted after additional adjustments for physical activity, outdoor PM2.5, environmental tobacco smoke, and health characteristics. Similar associations were observed for snoring and indoor PM2.5. ConclusionsChildren with higher indoor PM2.5 exposure had greater odds of sleep-disordered breathing and habitual loud snoring, suggesting that indoor air quality contributes to sleep disparities.

Age and sex differences in the effects of short- and long-term exposure to air pollution on endothelial dysfunction

BackgroundThe effects of air pollution on endothelial function remain unclear across populations. We aimed to use brachial artery flow-mediated dilatation (FMD) to identify demographic differences in the effects of air pollution exposure on endothelial dysfunction.MethodsWe measured FMD in 850 participants from October 2016 to January 2020. Location-specific concentrations of fine particulate matter < 2.5 μm aerodynamic diameter (PM2.5), inhalable particulate matter < 10 μm aerodynamic diameter (PM10), sulfur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (CO), and ozone (O3) measured by fixed ambient air monitoring stations were collected for short- and long-term exposure assessment. Multiple linear regression models and restricted cubic splines were used to assess the associations before and after stratification by age and sex.ResultsThis study eventually included 828 participants [551 (66.5%) younger than 65 years and 553 (66.8%) men]. Each 10 µg/m3 increase in 7-day exposure to PM2.5 and PM10 was significantly linearly associated with a 0.07% (β = -0.07, 95% CI: -0.13 to -0.004) and 0.05% (β = -0.05, 95% CI: -0.10 to -0.004) decrease in FMD in the fully adjusted model. After full adjustment, long-term exposure to all air pollutants was significantly associated with impaired FMD. Each 10 µg/m3 increase in long-term exposure to PM2.5 and PM10 was significantly associated with a -0.18% (95% CI: -0.34 to -0.03) and − 0.23% (95% CI: -0.40 to -0.06) change in FMD, respectively. After stratification, the associations of lower FMD with long-term exposure to PM2.5, PM10, SO2, NO2, and CO significantly persisted in men and participants younger than 65 years instead of women or older participants. For short-term exposure, we observed differences consistent with long-term exposure and a stronger effect of 7-day exposure to SO2 in men due to a significant interaction effect.ConclusionShort- and long-term exposure to different air pollutants are strongly associated with decreased endothelial function, and susceptibility to air pollution varies significantly with age and sex.

Ambient Air Pollution Exposures and Child Executive Function: A US Multicohort Study.

Executive function, which develops rapidly in childhood, enables problem-solving, focused attention, and planning. Animal models describe executive function decrements associated with ambient air pollution exposure, but epidemiologic studies are limited. We examined associations between early childhood air pollution exposure and school-aged executive function in 1235 children from three US pregnancy cohorts in the ECHO-PATHWAYS Consortium. We derived point-based residential exposures to ambient particulate matter ≤2.5 µm in aerodynamic diameter (PM 2.5 ), nitrogen dioxide (NO 2 ), and ozone (O 3 ) at ages 0-4 years from spatiotemporal models with a 2-week resolution. We assessed executive function across three domains, cognitive flexibility, working memory, and inhibitory control, using performance-based measures and calculated a composite score quantifying overall performance. We fitted linear regressions to assess air pollution and child executive function associations, adjusting for sociodemographic characteristics, maternal mental health, and health behaviors, and examined modification by child sex, maternal education, and neighborhood educational opportunity. In the overall sample, we found hypothesized inverse associations in crude but not adjusted models. Modified associations between NO 2 exposure and working memory by neighborhood education opportunity were present ( Pinteraction = 0.05), with inverse associations more pronounced in the "high" and "very high" categories. Associations of interest did not differ by child sex or maternal education. This work contributes to the evolving science regarding early-life environmental exposures and child development. There remains a need for continued exploration in future research endeavors, to elucidate the complex interplay between natural environment and social determinants influencing child neurodevelopment.

Air pollution, greenspace exposure and risk of Parkinson's disease: a prospective study of 441,462 participants.

The current understandings of the relationship between air pollution (AP), greenspace exposure and Parkinson's Disease (PD) remain inconclusive. We engaged 441,462 participants from the UK Biobank who were not diagnosed with PD. Utilizing Cox proportional hazard regression model, relationships between AP [nitrogen dioxide (NO2), and nitrogen oxides (NOX), particulate matter < 2.5μm in aerodynamic diameter(PM2.5), coarse particulate matter between 2.5μm and 10μm in aerodynamic diameter(PM2.5-10), particulate matter < 10μm in aerodynamic diameter(PM10)], greenspace exposure, and PD risk were determined independently. Our analyses comprised three models, adjusted for covariates, and affirmed through six sensitivity analyses to bolster the robustness of our findings. Moreover, mediation analysis was deployed to discern the mediating effect of AP between greenspaces and PD. During a median follow-up of 12.23years (5,574,293 person-years), there were 3,293 PD events. Each interquartile (IQR) increment in NO2 and PM10 concentrations were associated with 10% and 8% increase in PD onset risk, while the increases in NOX, PM2.5 and PM2.5-10 were not associated with PD risk. Additionally, greenspace may safeguard by reducing NO2 and PM10 levels, with the effect mediated by NO2 and PM10 in greenspace-PD relationship. Our findings indicate that an IQR increase in ambient NO2 and PM10 concentrations was associated with risk of PD development, while other pollutants (NOX, PM2.5 and PM2.5-10) were not associated with PD risk. Firstly, we find that augmented exposure to greenspace was associated with the lower PD risk by reducing NO2 and PM10 levels.

Semi-supervised urban haze pollution prediction based on multi-source heterogeneous data

Particulate matter (PM) is defined by the Texas Commission on Environmental Quality (TCEQ) as “a mixture of solid particles and liquid droplets found in the air”. These particles vary widely in size. Those particles that are less than 2.5 μm in aerodynamic diameter are known as Particulate Matter 2.5 or PM2.5. Urban haze pollution represented by PM2.5 is becoming serious, so air pollution monitoring is very important. However, due to high cost, the number of air monitoring stations is limited. Our work focuses on integrating multi-source heterogeneous data of Nanchang, China, which includes Taxi track, human mobility, Road networks, Points of Interest (POIs), Meteorology (e.g., temperature, dew point, humidity, wind speed, wind direction, atmospheric pressure, weather activity, weather conditions) and PM2.5 forecast data of air monitoring stations. This research presents an innovative approach to air quality prediction by integrating the above data sets from various sources and utilizing diverse architectures in Nanchang City, China. So for that, semi-supervised learning techniques will be used, namely collaborative training algorithm Co-Training (Co-T), who further adjusting algorithm Tri-Training (Tri-T). The objective is to accurately estimate haze pollution by integrating and using these multi-source heterogeneous data. We achieved this for the first time by employing a semi-supervised co-training strategy to accurately estimate pollution levels after applying the U-air system to environmental data. In particular, the algorithm of U-Air system is reproduced on these highly diverse heterogeneous data of Nanchang City, and the semi-supervised learning Co-T and Tri-T are used to conduct more detailed urban haze pollution prediction. Compared with Co-T, which train time classifier (TC) and subspace classifier (SC) respectively from the separated spatio-temporal perspective, the Tri-T is more accurate with a and faster because of its testing accuracy up to 85.62 %. The forecast results also present the potential of the city multi-source heterogeneous data and the effectiveness of the semi-supervised learning. We hope that this synthesis will motivate atmospheric environmental officials, scientists, and environmentalists in China to explore machine learning technology for controlling the discharge of pollutants and environmental management.

Associations between PM2.5 Components and Mortality of Ischemic Stroke, Chronic Obstructive Pulmonary Disease and Diabetes in Beijing, China.

Ischemic stroke (IS), chronic obstructive pulmonary disease (COPD) and diabetes mellitus (DM) account for a large burden of premature deaths. However, few studies have investigated the associations between fine particular matter (PM2.5) components and mortality of IS, COPD and DM. We aimed to examine these associations in Beijing, China. Data on daily mortality, air pollutants and meteorological factors from 2008 to 2011 in Beijing were collected. Daily concentrations of five PM2.5 components, namely, sulfate ion (SO42-), ammonium ion (NH4+), nitrate ion (NO3-), organic matter (OM) and black carbon (BC), were obtained from the Tracking Air Pollution (TAP) database in China. The association between PM2.5 components and daily deaths was explored using a quasi-Poisson regression with the distributed lag nonlinear model (DLNM). The average daily concentrations of SO42-, NH4+, NO3-, OM and BC were 11.24, 8.37, 12.00, 17.34 and 3.32 μg/m3, respectively. After adjusting for temperature, relative humidity, pressure, particulate matter less than 10 μm in aerodynamic diameter (PM10), nitrogen dioxide (NO2) and sulfur dioxide (SO2), an IQR increase in OM at lag day 2 and lag day 6 was associated with an increased DM mortality risk (RR 1.038; 95% CI: 1.005-1.071) and COPD mortality risk (RR 1.013; 95% CI: 1.001-1.026). An IQR increase in BC at lag day 0 and lag day 6 was associated with increased COPD mortality risk (RR 1.228; 95% CI: 1.017-1.48, RR 1.059; 95% CI: 1.001-1.121). Cumulative exposure to SO42- and NH4+ was associated with an increased mortality risk for IS, with the highest effect found for lag of 0-7 days (RR 1.085; 95% CI: 1.010-1.167, RR 1.083; 95% CI: 1.003-1.169). These effects varied by sex and age group. This study demonstrated associations of short-term exposure to PM2.5 components with increased risk of IS, COPD and DM mortality in the general population. Our study also highlighted susceptible subgroups.

Cross-shift changes in pulmonary function and occupational exposure to particulate matter among e-waste workers in Ghana.

Little is known on the association between cross-shift changes in pulmonary function and personal inhalation exposure to particulate matter (PM) among informal electronic-waste (e-waste) recovery workers who have substantial occupational exposure to airborne pollutants from burning e-waste. Using a cross-shift design, pre- and post-shift pulmonary function assessments and accompanying personal inhalation exposure to PM (sizes <1, <2.5 μm, and the coarse fraction, 2.5-10 μm in aerodynamic diameter) were measured among e-waste workers (n = 142) at the Agbogbloshie e-waste site and a comparison population (n = 65) in Accra, Ghana during 2017 and 2018. Linear mixed models estimated associations between percent changes in pulmonary function and personal PM. Declines in forced expiratory volume in one second (FEV1) and forced vital capacity (FVC) per hour were not significantly associated with increases in PM (all sizes) among either study population, despite breathing zone concentrations of PM (all sizes) that exceeded health-based guidelines in both populations. E-waste workers who worked "yesterday" did, however, have larger cross-shift declines in FVC [-2.4% (95%CI: -4.04%, -0.81%)] in comparison to those who did not work "yesterday," suggesting a possible role of cumulative exposure. Overall, short-term respiratory-related health effects related to PM exposure among e-waste workers were not seen in this sample. Selection bias due to the "healthy worker" effect, short shift duration, and inability to capture a true "pre-shift" pulmonary function test among workers who live at the worksite may explain results and suggest the need to adapt cross-shift studies for informal settings.

Predicting ambient PM2.5 concentrations via time series models in Anhui Province, China.

Due to rapid expansion in the global economy and industrialization, PM2.5 (particles smaller than 2.5µm in aerodynamic diameter) pollution has become a key environmental issue. The public health and social development directly affected by high PM2.5 levels. In this paper, ambient PM2.5 concentrations along with meteorological data are forecasted using time series models, including random forest (RF), prophet forecasting model (PFM), and autoregressive integrated moving average (ARIMA) in Anhui province, China. The results indicate that the RF model outperformed the PFM and ARIMA in the prediction of PM2.5 concentrations, with cross-validation coefficients of determination R2, RMSE, and MAE values of 0.83, 10.39µg/m3, and 6.83µg/m3, respectively. PFM achieved the average results (R2 = 0.71, RMSE = 13.90µg/m3, and MAE = 9.05µg/m3), while the predicted results by ARIMA are comparatively poorer (R2 = 0.64, RMSE = 15.85µg/m3, and MAE = 10.59µg/m3) than RF and PFM. These findings reveal that the RF model is the most effective method for predicting PM2.5 and can be applied to other regions for new findings.

Interchanging Reusable and Disposable Nebulizers Used with Home-Based Compressors May Result in Inconsistent Dosing: A Laboratory Investigation with Device Combinations Supplied to the US Healthcare Environment.

Reusable nebulizer-compressor combinations deliver inhaled medications for patients with chronic lung diseases. On hospital discharge, the patient may take home the disposable nebulizer that was packagedand combine it with their home compressor. Though this practice may reduce waste, it can increase variability in medication delivery. Our study compared several reusable and disposable nebulizers packaged with compressor kits used in the US. We included a common disposable hospital nebulizer that may not be supplied with popular home kits but may be brought home after a hospitalization or emergency department visit. We focused on fine droplet mass < 4.7 μm aerodynamic diameter (FDM<4.7 μm), associated with medication delivery to the airways of the lungs. We evaluated the following nebulizer-compressor combinations (n = 5 replicates): 1. OMBRA® Table Top Compressor with MC 300® reusable and Airlife™ MistyMax™ 10® disposable nebulizer, 2. Sami-the-Seal® compressor with SideStream® reusable and disposable nebulizers and Airlife™ MistyMax 10™ disposable nebulizer, 3. VIOS® compressor with LC Sprint® reusable, and VixOne® and Airlife™ MistyMax™ disposable nebulizers, 4. Innospire® Elegance® compressor with SideStream® reusable and disposable nebulizers and Airlife™ MistyMax 10™ disposable nebulizer, 5. Willis-the-Whale® compressor with SideStream® reusable and disposable nebulizers and Airlife™ MistyMax 10™ disposable nebulizer, 6. Pari PRONEB® Max compressor with LC Sprint® reusable and Airlife™ MistyMax 10™ disposable nebulizer. We placed a 3-ml albuterol solution (0.833 mg/ml) in each nebulizer. A bacterial/viral filter was attached to the nebulizer mouthpiece to capture emitted medication, with the filter exit coupled to a simulator of a tidal breathing adult (rate = 10 cycles/min; Vt = 600 ml; I/E ratio = 1:2). The filter was replaced at 1-min intervals until onset of sputter. Droplet size distributions (n = 5 replicates/system) were determined in parallel by laser diffractometry. Cumulative FDM<4.7 μm varied from 381 ± 33 μg for the best performing combination (Proneb/LC-Sprint) to 150 ± 21 μg for the system with the lowest output (VIOS®/MistyMax 10™). Substituting one nebulizer for another can result in large differences in medication delivery to the lungs.

Assessment of census-tract level socioeconomic position as a modifier of the relationship between short-term PM2.5 exposure and cardiovascular emergency department visits in Missouri

IntroductionAmbient particulate matter ≤ 2.5 µm in aerodynamic diameter (PM2.5) exposure elevates the risk for cardiovascular disease morbidity (CVDM). The aim of this study is to characterise which area-level measures...

Air Pollution Exposure and Interstitial Lung Features in SPIROMICS Participants with Chronic Obstructive Pulmonary Disease.

Rationale: It is unknown whether air pollution is associated with radiographic features of interstitial lung disease in individuals with chronic obstructive pulmonary disease (COPD). Objectives: To determine whether air pollution increases the prevalence of interstitial lung abnormalities (ILA) or percent high-attenuation areas (HAA) on computed tomography (CT) in individuals with a heavy smoking history and COPD. Methods: We performed a cross-sectional study of SPIROMICS (Subpopulations and Intermediate Outcome Measures in COPD Study), focused on current or former smokers with COPD. Ten-year exposure to particulate matter ⩽2.5 μm in aerodynamic diameter (PM2.5), nitrogen oxides (NOx), nitrogen dioxide (NO2), and ozone before enrollment CT (completed between 2010 and 2015) were estimated with validated spatiotemporal models at residential addresses. We applied adjusted multivariable modified Poisson regression and linear regression to investigate associations between pollution exposure and relative risk (RR) of ILA or increased percent HAA (between -600 and -250 Hounsfield units), respectively. We assessed for effect modification by MUC5B-promoter polymorphism (variant allele carriers GT or TT vs. GG at rs3705950), smoking status, sex, and percent emphysema. Results: Among 1,272 participants with COPD assessed for HAA, 424 were current smokers, and 249 were carriers of the variant MUC5B allele. A total of 519 participants were assessed for ILA. We found no association between pollution exposure and ILA or HAA. Associations between pollutant exposures and risk of ILA were modified by the presence of MUC5B polymorphism (P value interaction term for NOx = 0.04 and PM2.5 = 0.05) and smoking status (P value interaction term for NOx = 0.05; NO2 = 0.01; and ozone = 0.05). With higher exposure to NOx and PM2.5, MUC5B variant carriers had an increased risk of ILA (RR per 26 ppb NOx, 2.41; 95% confidence interval [CI], 0.97-6.0; and RR per 4 μg ⋅ m-3 PM2.5, 1.43; 95% CI, 0.93-2.2, respectively). With higher exposure to NO2, former smokers had an increased risk of ILA (RR per 10 ppb, 1.64; 95% CI, 1.0-2.7). Conclusions: Exposure to ambient air pollution was not associated with interstitial features on CT in this population of heavy smokers with COPD. MUC5B modified the association between pollution and ILA, suggesting that gene-environment interactions may influence prevalence of interstitial lung features in COPD.

Characterizing the Atmospheric Mn Cycle and Its Impact on Terrestrial Biogeochemistry

AbstractThe role of manganese (Mn) in ecosystem carbon (C) biogeochemical cycling is gaining increasing attention. While soil Mn is mainly derived from bedrock, atmospheric deposition could be a major source of Mn to surface soils, with implications for soil C cycling. However, quantification of the atmospheric Mn cycle, which comprises emissions from natural (desert dust, sea salts, volcanoes, primary biogenic particles, and wildfires) and anthropogenic sources (e.g., industrialization and land‐use change due to agriculture), transport, and deposition, remains uncertain. Here, we use compiled emission data sets for each identified source to model and quantify the atmospheric Mn cycle by combining an atmospheric model and in situ atmospheric concentration measurements. We estimated global emissions of atmospheric Mn in aerosols (&lt;10 μm in aerodynamic diameter) to be 1,400 Gg Mn year−1. Approximately 31% of the emissions come from anthropogenic sources. Deposition of the anthropogenic Mn shortened Mn “pseudo” turnover times in 1‐m‐thick surface soils (ranging from 1,000 to over 10,000,000 years) by 1–2 orders of magnitude in industrialized regions. Such anthropogenic Mn inputs boosted the Mn‐to‐N ratio of the atmospheric deposition in non‐desert dominated regions (between 5 × 10−5 and 0.02) across industrialized areas, but that was still lower than soil Mn‐to‐N ratio by 1–3 orders of magnitude. Correlation analysis revealed a negative relationship between Mn deposition and topsoil C density across temperate and (sub)tropical forests, consisting with atmospheric Mn deposition enhancing carbon respiration as seen in in situ biogeochemical studies.

Long-Term Particulate Matter Exposure and Mortality in Hospitalized Patients with COVID-19 in South Korea.

Rationale: Particulate matter (PM) exposure exacerbates health outcomes by causing lung damage. Objectives: To investigate whether prior exposure to particulate matter ⩽10 μm and ⩽2.5 μm in aerodynamic diameter (PM10 and PM2.5) was associated with clinical outcomes among patients with coronavirus disease (COVID-19). Methods: Data from the nationwide registration database of the National Health Insurance and Korea Disease Control and Prevention Agency in South Korea were used. The study included adult patients who were admitted to monitoring centers or hospitals between October 8, 2020 and December 31, 2021, after COVID-19 confirmation. AirKOREA database, which compiles air pollutant data from 642 stations in 162 cities and counties across South Korea, was used to extract data on PM levels. Average values of monthly exposure to PM10 and PM2.5 from the year previous to hospital admission because of COVID-19 to the date of confirmation of COVID-19 were calculated and used to define PM exposures of patients with COVID-19. Results: In total, 322,289 patients with COVID-19 were included, and 4,633 (1.4%) died during hospitalization. After adjusting for covariates, a 1-μg/m3 increase in PM10 and PM2.5 exposure was associated with 4% (odds ratio [OR], 1.04; 95% confidence interval [CI], 1.03-1.05; P < 0.001) and 6% (OR, 1.06; 95% CI, 1.04-1.07; P < 0.001) increase in the risk of in-hospital mortality, respectively. In addition, a 1-μg/m3 increase in PM10 and PM2.5 was associated with 5% (OR, 1.05; 95% CI, 1.04-1.07; P < 0.001) and 8% (OR, 1.08; 95% CI, 1.06-1.10; P < 0.001) increase in the risks of requiring intensive care unit (ICU) admission and mechanical ventilation, respectively. Conclusions: PM10 and PM2.5 exposure was associated with increased in-hospital mortality and the need for ICU admission and mechanical ventilation among patients with COVID-19 in South Korea.

Inhaled dry powder liposomal azithromycin for treatment of chronic lower respiratory tract infection

A dry powder inhaled liposomal azithromycin formulation was developed for the treatment of chronic respiratory diseases such as cystic fibrosis and bronchiectasis. Key properties including liposome size, charge and encapsulation efficiency powder size, shape, glass transition temperature (Tg), water content and in vitro respiratory deposition were determined. Antimicrobial activity against cystic fibrosis (CF) respiratory pathogens was determined by MIC, MBC and biofilm assays. Cytotoxicity and cellular uptake studies were performed using A549 cells. The average liposome size was 105 nm, charge was 55 mV and encapsulation efficiency was 75 %. The mean powder particle size d[v,50] of 4.54 µm and Mass Median Aerodynamic Diameter (MMAD) was 5.23 µm with a mean Tg of 76˚C and water content of 2.1 %. These excellent physicochemical characteristics were maintained over one year. Liposomal loaded azithromycin demonstrated enhanced activity against P. aeruginosa clinical isolates grown in biofilm. The formulation was rapidly delivered into bacterial cells with > 75 % uptake in 1 h. Rapid uptake into A549 cells via a cholesterol-dependent endocytosis pathway with no cytotoxic effects apparent. These data demonstrate that this formulation could offer benefits over current treatment regimens for people with chronic respiratory infection.

Spatiotemporal variations in emission and particulate matter concentration outside a concentrated layer feeding operation

A year-round monitoring of Particulate Matter (PM) less than 2.5 μm in aerodynamic diameter (PM2.5) and Total Suspended Particulate (TSP) from a conventional cage laying hen house was conducted to reveal their spatiotemporal variations of concentrations downwind of tunnel fans. The PM Emission Rate (ER) and the correlations between PM with meteorological parameters and ventilation rate were studied. Ten self-developed Particle Concentration Monitoring Units were distributed to multiple horizontal (2, 25, and 50 m) and vertical (2 and 5 m) locations for PM examination. Four PM2.5 concentration categories were classified: good (0–35 μg m−3), moderate (35–75 μg m−3), unhealthy (75–150 μg m−3), and very unhealthy (150–350 μg m−3). Annual and monthly percentages of PM2.5 and TSP sampling hours for each category were calculated. Significant temporal variations in ER were observed, with monthly average ER ranging from 0.05 to 0.86 mg d−1 hen−1 for PM2.5 and 1.40–8.90 mg d−1 hen−1 for TSP. Approximately 10–40% of PM2.5 sampling hours exceeded 75 μg m−3, while no TSP concentration was higher than the recommended threshold. The monthly percentage for the “very unhealthy” PM2.5 category was higher in winter, whereas the highest monthly percentage for the 800–1,200 μg m−3 TSP category was found in summer. Higher PM2.5 concentrations were prone to be observed at further sampling points, while higher TSP concentrations were mostly detected near the fans or on both sides of the sampling area. PM2.5 and TSP were positively correlated with ambient temperature and ventilation rate, while negatively correlated with relative humidity.