Μm In Aerodynamic Diameter Research Articles

Short-Term Exposure to Wildfire Smoke and and Cognitive Performance in a Brain-Training Game: A Longitudinal Study of U.S. Adults.

Background:There is increasing evidence that long-term exposure to fine particulate matter [PM in aerodynamic diameter ()] may adversely impact cognitive performance. Wildfire smoke is one of the biggest sources of and concentrations are likely to increase under climate change. However, little is known about how short-term exposure impacts cognitive function.Objectives:We aimed to evaluate the associations between daily and subdaily (hourly) and wildfire smoke exposure and cognitive performance in adults.Methods:Scores from 20 plays of an attention-oriented brain-training game were obtained for 10,228 adults in the United States (U.S.). We estimated daily and hourly exposure through a data fusion of observations from multiple monitoring networks. Daily smoke exposure in the western U.S. was obtained from satellite-derived estimates of smoke plume density. We used a longitudinal repeated measures design with linear mixed effects models to test for associations between short-term exposure and attention score. Results were also stratified by age, gender, user behavior, and region.Results:Daily and subdaily were negatively associated with attention score. A increase in in the 3 h prior to gameplay was associated with a 21.0 [95% confidence interval (CI): 3.3, 38.7]-point decrease in score. exposure over 20 plays accounted for an estimated average 3.7% (95% CI: 0.7%, 6.7%) reduction in final score. Associations were more pronounced in the wildfire-impacted western U.S. Medium and heavy smoke density were also negatively associated with score. Heavy smoke density the day prior to gameplay was associated with a 117.0 (95% CI: 1.7, 232.3)-point decrease in score relative to no smoke. Although differences between subgroups were not statistically significant, associations were most pronounced for younger (18–29 y), older (), habitual, and male users.Discussion:Our results indicate that and wildfire smoke were associated with reduced attention in adults within hours and days of exposure, but further research is needed to elucidate these relationships. https://doi.org/10.1289/EHP10498

Association of Ambient Particulate Matter Pollution of Different Sizes With In-Hospital Case Fatality Among Stroke Patients in China.

To characterize the association of ambient particulate matter (PM) pollution of different sizes (PM ≤1 µm in aerodynamic diameter [PM1], PM2.5, and PM10) with in-hospital case fatality among patients with stroke in China. We collected hospitalizations due to stroke in 4 provinces in China from 2013 to 2019. Seven-day and annual averages of PM prior to hospitalization were estimated using bilinear interpolation and residential addresses. Associations with in-hospital case fatality were estimated using random-effects logistic regression models. Potential reducible fraction and the number of fatalities attributed to PM were estimated using a counterfactual approach. Among 3,109,634 stroke hospitalizations (mean age 67.23 years [SD 12.22]; 1,765,644 [56.78%] male), we identified 32,140 in-hospital stroke fatalities (case fatality rate 1.03%). Each 10 µg/m3 increase in 7-day average (short-term) exposure to PM was associated with increased in-hospital case fatality: odds ratios (ORs) were 1.058 (95% CI 1.047-1.068) for PM1, 1.037 (95% CI 1.031-1.043) for PM2.5, and 1.025 (95% CI 1.021-1.029) for PM10. Similar but larger ORs were observed for annual averages (long-term): 1.240 (95% CI 1.217-1.265) for PM1, 1.105 (95% CI 1.094-1.116) for PM2.5, and 1.090 (95% CI 1.082-1.099) for PM10. In counterfactual analyses, PM10 was associated with the largest potential reducible fraction in in-hospital case fatality (10% [95% CI 8.3-11.7] for short-term exposure and 21.1% [19.1%-23%] for long-term exposure), followed by PM1 and PM2.5. PM pollution is a risk factor for in-hospital stroke-related deaths. Strategies that target reducing PM pollution may improve the health outcomes of patients with stroke.

Measurement report: Vertical profiling of particle size distributions over Lhasa, Tibet – tethered balloon-based in situ measurements and source apportionment

Abstract. In situ measurements of vertically resolved particle size distributions based on a tethered balloon system were carried out for the first time in the highland city of Lhasa over the Tibetan Plateau in summer 2020, using portable optical counters for the size range of ​​​​​​​0.124–32 µm. The vertical structure of 112 aerosol profiles was found to be largely shaped by the evolution of the planetary boundary layer (PBL), with a nearly uniform distribution of aerosols within the daytime mixing layer and a sharp decline with the height in the shallow nocturnal boundary layer. During the campaign, mass concentrations of particulate matter smaller than 2.5 µm in aerodynamic diameter (PM2.5) within the PBL ranged from 0.5 to 12.0 µg m−3, with an average and standard deviation of 3.4 ± 2.3 µg m−3, almost 4 times the amount in the free troposphere (FT), which was rarely affected by surface anthropogenic emissions. Though there was a lower level of particle mass in the residual layer (RL) than in the PBL, a similarity in particle mass size distributions (PMSDs) suggested that particles in the RL might be of the same origin as the particles in the PBL. This was also consistent with the source apportionment analysis based on the PMSDs. In total, three distinct modes were observed in the PMSDs for the PBL and the RL. One mode was exclusively coarse particles up to roughly 15 µm, peaking around 5 µm. More than 50 % of total particle mass was often contributed by coarse-mode particles in this area, which was thought to be associated with local dust resuspension. The mode peaking over 0.5–0.7 µm was representative of biomass burning on religious holidays and was found to be most pronounced on holiday mornings. The contribution from the religious burning factor rose from about 25 % on non-holidays to nearly 50 % on holiday mornings. The mode dominated by particles smaller than 0.3 µm was thought to be associated with combustion-related emissions and/or secondary aerosol formation. In the FT coarse mode, particles only accounted for less than 10 % of the total mass, and particles larger than 5 µm were negligible. The predominant submicron particles in the FT might be related to secondary aerosol formation and the aging of existing particles. To give a full picture of aerosol physical and chemical properties and better understand the origin and impacts of aerosols in this area, intensive field campaigns involving measurements of vertically resolved aerosol chemical compositions in different seasons would be highly encouraged in the future.

Ambient Air Pollutant Exposures and COVID-19 Severity and Mortality in a Cohort of Patients with COVID-19 in Southern California.

Rationale: Ecological studies have shown air pollution associations with coronavirus disease (COVID-19) outcomes. However, few cohort studies have been conducted. Objectives: To conduct a cohort study investigating the association between air pollution and COVID-19 severity using individual-level data from the electronic medical record. Methods: This cohort included all individuals who received diagnoses of COVID-19 from Kaiser Permanente Southern California between March 1 and August 31, 2020. One-year and 1-month averaged ambient air pollutant (particulate matter ⩽2.5 μm in aerodynamic diameter [PM2.5], NO2, and O3) exposures before COVID-19 diagnosis were estimated on the basis of residential address history. Outcomes included COVID-19-related hospitalizations, intensive respiratory support (IRS), and ICU admissions within 30 days and mortality within 60 days after COVID-19 diagnosis. Covariates included socioeconomic characteristics and comorbidities. Measurements and Main Results: Among 74,915 individuals (mean age, 42.5 years; 54% women; 66% Hispanic), rates of hospitalization, IRS, ICU admission, and mortality were 6.3%, 2.4%, 1.5%, and 1.5%, respectively. Using multipollutant models adjusted for covariates, 1-year PM2.5 and 1-month NO2 average exposures were associated with COVID-19 severity. The odds ratios associated with a 1-SD increase in 1-year PM2.5 (SD, 1.5 μg/m3) were 1.24 (95% confidence interval [CI], 1.16-1.32) for COVID-19-related hospitalization, 1.33 (95% CI, 1.20-1.47) for IRS, and 1.32 (95% CI, 1.16-1.51) for ICU admission; the corresponding odds ratios associated with 1-month NO2 (SD, 3.3 ppb) were 1.12 (95% CI, 1.06-1.17) for hospitalization, 1.18 (95% CI, 1.10-1.27) for IRS, and 1.21 (95% CI, 1.11-1.33) for ICU admission. The hazard ratios for mortality were 1.14 (95% CI, 1.02-1.27) for 1-year PM2.5 and 1.07 (95% CI, 0.98-1.16) for 1-month NO2. No significant interactions with age, sex or ethnicity were observed. Conclusions: Ambient PM2.5 and NO2 exposures may affect COVID-19 severity and mortality.

Efficacy of Air Filtration and Education Interventions on Indoor Fine Particulate Matter and Child Lower Respiratory Tract Infections among Rural U.S. Homes Heated with Wood Stoves: Results from the KidsAIR Randomized Trial.

Background:Millions of rural U.S. households are heated with wood stoves. Wood stove use can lead to high indoor concentrations of fine particulate matter [airborne particles in aerodynamic diameter ()] and is associated with lower respiratory tract infection (LRTI) in children.Objectives:We assessed the impact of low-cost educational and air filtration interventions on childhood LRTI and indoor in rural U.S. homes with wood stoves.Methods:The Kids Air Quality Interventions for Reducing Respiratory Infections (KidsAIR) study was a parallel three-arm (education, portable air filtration unit, control), post-only randomized trial in households from Alaska, Montana, and Navajo Nation (Arizona and New Mexico) with a wood stove and one or more children of age. We tracked LRTI cases for two consecutive winter seasons and measured indoor over a 6-d period during the first winter. We assessed results using two analytical frameworks: a) intervention efficacy on LRTI and (intent-to-treat), and b) association between and LRTI (exposure–response).Results:There were 61 LRTI cases from 14,636 child-weeks of follow-up among 461 children. In the intent-to-treat analysis, children in the education arm [; 95% confidence interval (CI): 0.35, 2.72] and the filtration arm (; 95% CI: 0.46, 3.32) had similar odds of LRTI vs. control. Geometric mean concentrations were similar to control in the education arm (11.77% higher; 95% CI: , 49.72) and air filtration arm (6.96% lower; 95% CI: , 24.55). In the exposure–response analysis, odds of LRTI were 1.45 times higher (95% CI: 1.02, 2.05) per interquartile range () increase in mean indoor .Discussion:We did not observe meaningful differences in LRTI or indoor in the air filtration or education arms compared with the control arm. Results from the exposure–response analysis provide further evidence that biomass air pollution adversely impacts childhood LRTI. Our results highlight the need for novel, effective intervention strategies in households heated with wood stoves. https://doi.org/10.1289/EHP9932

Aerosol particle properties at a remote tropical rainforest in Borneo

This paper aims to investigate aerosol particle properties and their seasonal variabilities at a remote tropical forest site. It also attempts to study the relationship between aerosol particles and dynamic atmospheric processes that modulate aerosol variability. Mass concentrations for particles smaller than 10 μm aerodynamic diameter (PM10) and optical aerosol particle properties were measured at Danum Valley tropical rainforest in Borneo Island. The particle mass concentrations were measured using a Tapered Element Oscillating Microbalance (TEOM). Measurements of aerosol particle optical properties, i.e., the particle light absorption and scattering coefficients, were conducted using a Multi-Angle Absorption Photometer (MAAP) and nephelometer, respectively. The single scattering albedo (SSA) and scattering Angstrom exponent (SAE) were calculated from the aerosol scattering and absorption coefficients. The results showed that the daily average of PM10 mass concentrations was 12.3 μgm−3, while the particle light absorption coefficients at wavelength 637 nm and scattering coefficients at wavelength 525 nm were reported as 2.7 Mm−1 and 21.7 Mm−1, respectively. The daily average SSA and SAE recorded were 0.89 and 1.44, respectively. The SSA showed no seasonal variations while higher SAE was observed during the dry season due to the influence of biomass burning originating from the southern region of Borneo. The wavelet analysis showed strong intra-seasonal cycles (12–20 and 32–64 days) which suggest the influence of Quasi-BiWeekly (QBW) oscillation and Madden-Julian Oscillation (MJO) on the aerosol variability over the tropics. The analysis also showed seasonal and annual variability bands, generally associated with the dry and wet seasons over the region.

Evaluating the PurpleAir monitor as an aerosol light scattering instrument

Abstract. The Plantower PMS5003 sensors (PMS) used in the PurpleAir monitor PA-II-SD configuration (PA-PMS) are equivalent to cell-reciprocal nephelometers using a 657 nm perpendicularly polarized light source that integrates light scattering from 18 to 166∘. Yearlong field data at the National Oceanic and Atmospheric Administration's (NOAA) Mauna Loa Observatory (MLO) and Boulder Table Mountain (BOS) sites show that the 1 h average of the PA-PMS first size channel, labeled “> 0.3 µm” (“CH1”), is highly correlated with submicrometer aerosol scattering coefficients at the 550 and 700 nm wavelengths measured by the TSI 3563 integrating nephelometer, from 0.4 to 500 Mm−1. This corresponds to an hourly average submicrometer aerosol mass concentration of approximately 0.2 to 200 µg m−3. A physical–optical model of the PMS is developed to estimate light intensity on the photodiode, accounting for angular truncation of the volume scattering function as a function of particle size. The model predicts that the PMS response to particles > 0.3 µm decreases relative to an ideal nephelometer by about 75 % for particle diameters ≥ 1.0 µm. This is a result of using a laser that is polarized, the angular truncation of the scattered light, and particle losses (e.g., due to aspiration) before reaching the laser. It is shown that CH1 is linearly proportional to the model-predicted intensity of the light scattered by particles in the PMS laser to its photodiode over 4 orders of magnitude. This is consistent with CH1 being a measure of the scattering coefficient and not the particle number concentration or particulate matter concentration. The model predictions are consistent with data from published laboratory studies which evaluated the PMS against a variety of aerosols. Predictions are then compared with yearlong fine aerosol size distribution and scattering coefficient field data at the BOS site. Field data at BOS confirm the model prediction that the ratio of CH1 to the scattering coefficient would be highest for aerosols with median scattering diameters < 0.3 µm. The PMS detects aerosols smaller than 0.3 µm diameter in proportion to their contribution to the scattering coefficient. The results of this study indicate that the PMS is not an optical particle counter and that its six size fractions are not a meaningful representation of particle size distribution. The relationship between the PMS 1 h average CH1 and bsp1, the scattering coefficient in Mm−1 due to particles below 1 µm aerodynamic diameter, at wavelength 550 nm, is found to be bsp1 = 0.015 ± 2.07 × 10−5 × CH1, for relative humidity below 40 %. The coefficient of determination r2 is 0.97. This suggests that the low-cost and widely used PA monitors can be used to measure and predict the submicron aerosol light scattering coefficient in the mid-visible nearly as well as integrating nephelometers. The effectiveness of the PA-PMS to serve as a PM2.5 mass concentration monitor is due to both the sensor behaving like an imperfect integrating nephelometer and the mass scattering efficiency of ambient PM2.5 aerosols being roughly constant.

TD-GC/MS analysis of indoor air pollutants (VOCs, PM) in hair salons

Hairdressing personnel is daily exposed to various chemical air pollutants, and specifically to Volatile Organic Compounds (VOCs) and Particulate Matter (PM) in hair salons. This is of concern, due to the hazardous effects of these chemicals on the individual's health. Nevertheless, a limited exposure assessment of indoor air quality (IAQ) has been performed. The aim of this study was to analyze the indoor air in 5 hair salons, to assess the IAQ of the occupational exposure, and to identify the main VOCs produced or activities responsible for the respective indoor pollution. The chemical analysis took place inside the salon environment by monitoring the emitted VOCs, as well as the PM of 1, 2.5, 4, and 10 μm aerodynamic diameter. The sampling of VOCs was performed by adsorption of pollutants on Tenax TA sorbent tubes, that were subsequently analyzed using a thermal desorption unit coupled to gas chromatography/mass spectrometry (TD-GC/MS). The obtained results showed that hair products are a major source of air pollutants, as elevated concentrations of VOCs and PM are released in the working environment. Furthermore, the type and concentration of VOCs are affected by the various hair treatment activities taking place in the salons. Among the main compounds detected there was benzene, toluene, ethylbenzene, and xylenes, known as BTEX, as well as, diethyl phthalate, 1,4-dioxane, etc. More than 50 VOCs were identified (occurrence ≥60%) and 14 of them were quantified. Their average concentration levels varied from 12 μg m−3 for naphthalene to 941 μg m−3 for toluene. The measuring levels for PM revealed violations of the EPA and WHO international standards for permissible limit concentrations; this was the case in all hair treatment activities but mostly during keratin treatment. Hence, much more effort is needed to reduce the respective concentration levels of PM and VOCs, that contribute to self-reported health problems.

Machine Learning Models for Predicting the Occurrence of Respiratory Diseases Using Climatic and Air-Pollution Factors

ObjectivesBecause climatic and air-pollution factors are known to influence the occurrence of respiratory diseases, we used these factors to develop machine learning models for predicting the occurrence of respiratory diseases.MethodsWe obtained the daily number of respiratory disease patients in Seoul. We used climatic and air-pollution factors to predict the daily number of patients treated for respiratory diseases per 10,000 inhabitants. We applied the relief-based feature selection algorithm to evaluate the importance of feature selection. We used the gradient boosting and Gaussian process regression (GPR) methods, respectively, to develop two different prediction models. We also employed the holdout cross-validation method, in which 75% of the data was used to train the model, and the remaining 25% was used to test the trained model. We determined the estimated number of respiratory disease patients by applying the developed prediction models to the test set. To evaluate the performance of each model, we calculated the coefficient of determination (R2) and the root mean square error (RMSE) between the original and estimated numbers of respiratory disease patients. We used the Shapley Additive exPlanations (SHAP) approach to interpret the estimated output of each machine learning model.ResultsFeatures with negative weights in the relief-based algorithm were excluded. When applying gradient boosting to unseen test data, R2 and RMSE were 0.68 and 13.8, respectively. For GPR, the R2 and RMSE were 0.67 and 13.9, respectively. SHAP analysis showed that reductions in average temperature, daylight duration, average humidity, sulfur dioxide (SO2), total solar insolation amount, and temperature difference increased the number of respiratory disease patients, whereas increases in atmospheric pressure, carbon monoxide (CO), and particulate matter ≤2.5 μm in aerodynamic diameter (PM2.5) increased the number of respiratory disease patients.ConclusionWe successfully developed models for predicting the occurrence of respiratory diseases using climatic and air-pollution factors. These models could evolve into public warning systems.

Associations of air pollutants with pneumonia hospital admissions in Qingdao, China: a prospective cohort study.

Studies about the pneumonia morbidity effects of various air pollution exposure are still limited in China. We aimed to explore the short-term effect of air pollutants exposure on pneumonia admission and identify the vulnerable groups in Qingdao, China. From January 2015 to October 2017, a prospective cohort involving 433,032 participants across 3 counties in Qingdao were enrolled in the study. Distributed lag nonlinear model (DLNM) was applied to assess the associations between air pollutants and pneumonia hospitalizations. There were 636 cases of pneumonia, with an annual incidence density of 54.33 per 100,000 person-years (95% CI: 50.11, 58.56). A 10μg/m3 increment of sulfur dioxide (SO2) distributed at a 4-week lag in Qingdao was associated with increased pneumonia hospitalizations, with a risk ratio of 2.10 (95% CI: 1.06, 4.13). Subgroup analyses indicate that PM ≤ 2.5μm in aerodynamic diameter and SO2 showed stronger effects on pneumonia in females than males, whereas people in urban regions were more vulnerable to nitrogen dioxide and ozone (O3) than the others. We also observed distinct acute effects and harvesting effects of SO2 and O3 on pneumonia in urban areas. Strategies should be taken to further reduce levels of ambient PM2.5, SO2, and O3.

Direct measurement of the deposition of submicron soot particles on leaves of Platanus acerifolia tree.

Submicron soot particles (<1.0 μm in aerodynamic diameter) are responsible for global warming and health burdens worldwide. However, studies on bio-monitoring of submicron soot particles and their associated sources by using tree leaves are not comprehensively illustrated. Here, we determined the seasonal trends of submicron soot particles on the leaves of the Platanus acerifolia collected from two cities (Lu'an, Anhui Province, and Nanjing, Jiangsu Province) in the Yangtze River Delta region, China. The source apportionment of submicron soot particles was performed using stable carbon isotopic analyses. Significant seasonal trends of submicron soot particles were observed in two cities with averaged levels of 0.41-1.36 mg m-2 in cold seasons and averaged levels of 0.13-0.24 mg m-2 in warm seasons. The levels of δ13C for submicron soot at the suburban site of Lu'an city were observed to be in the range of -25.6‰ to -18.2‰ with fossil fuels dominated (∼58%) in summer and -23.0‰ to -15.6‰ with biomass burning dominated in winter (∼67%). In comparison, the ranges in the levels of δ13C in submicron soot were found to be from -26.5‰ to -20.4‰ in winter, and -24.2‰ to -17.9‰ in summer at the urban site of Nanjing. Fossil fuels accounted for a large fraction of submicron soot with average contributions of 53% in winter and 73% in summer, respectively. These findings demonstrate that Platanus acerifolia trees could be used as an effective and low-cost bio-monitoring tool for monitoring the pollution status of submicron soot and associated source contribution.

Child Survival and Early Lifetime Exposures to Ambient Fine Particulate Matter in India: A Retrospective Cohort Study.

Background:Ambient fine particulate matter [PM in aerodynamic diameter ()] is a major health risk for children, particularly in South Asia, which currently experiences the highest levels globally. Nevertheless, there is comparatively little epidemiological evidence from this region to quantify the effects of on child survival.Objectives:We estimated the association between exposure and child survival in India.Methods:We constructed a large, retrospective, and nationally representative cohort of children , born between 2009–2016, from the publicly available, cross-sectional 2015–2016 Demographic Health Surveys in India. In utero and post-delivery lifetime average ambient exposures were estimated with data from satellite remote sensing, meteorology, and land use information (model 0.82). We used Cox proportional hazards regression to estimate the association between both average in utero and post-delivery lifetime and all-cause child mortality, controlling for individual- and household-level covariates, seasonality, location, and meteorology.Results:Over 7,447,724 child-months of follow-up, there were 11,559 deaths at reported by the children’s mothers. The mean concentrations of 9-month in utero and post-delivery lifetime average ambient exposure were (range: ) and (range: ), respectively. Estimated child mortality adjusted hazard ratios were 1.023 [95% confidence interval (CI): 1.008, 1.038] and 1.013 (95% CI: 1.001, 1.026) per increase of in utero and post-delivery lifetime , with both exposures in the model.Discussion:This study adds to the growing body of evidence about the adverse health effects of by demonstrating the association between exposure, both in utero and post-delivery, on child survival at the national level in India. Strategies to reduce ambient air pollution levels, including steps to minimize in utero and early life exposures, are urgently needed in India and other countries where exposures are above recommended guideline values. https://doi.org/10.1289/EHP8910

Exposure to during Pregnancy and Fetal Growth in Eastern Massachusetts, USA.

Background:Prior studies have examined the association between fine particulate matter [PM in aerodynamic diameter ()] and fetal growth with either limited spatial or temporal resolution.Objectives:In this study, we examined the association between exposure during pregnancy and fetal growth measures (ultrasound parameters and birth weight) in a pregnancy cohort using spatiotemporally resolved in Eastern Massachusetts, USA.Methods:We used ultrasound measures of biparietal diameter (BPD), head circumference, femur length, and abdominal circumference (AC), in addition to birth weight, from 9,446 pregnancies that were delivered at the Beth Israel Deaconess Medical Center from 2011–2016. We used linear mixed-effects models to examine the associations of in two exposure windows (the first 16 wk of pregnancy and the cumulative exposure up until the assessment of fetal growth) with anatomic scans (ultrasound ), growth scans (ultrasound ), and birth weight. All models were adjusted for sociodemographic characteristics, long-term trends, and temperature.Results:Higher exposure in the first 16 wk was associated with smaller fetal growth measures, where associations were particularly strong for BPD, AC, and birth weight. For example, a increase in was associated with a lower mean BPD -score of (95% CI: , ) before 24 wk, a lower mean AC -score of (95% CI: , ) after 24 wk, and a lower mean birth weight -score of (95% CI: , ). Analyses examining the associations with cumulative exposure up until the assessment of fetal growth produced attenuated associations.Conclusions:Higher gestational exposure to was associated with smaller fetal growth measures at levels below the current national standards. https://doi.org/10.1289/EHP9824

Filtration and Breathability of Nonwoven Fabrics Used in Washable Masks

We consider fabrics that can improve upon the performance of the widespread all-cotton mask, and examines the effect of layering, machine washing and drying on their filtration and breathability. Individual materials were evaluated for their quality factor, Q, which combines filtration efficiency and breathability. Filtration was tested against particles 0.5 μm to 5 μm aerodynamic diameter. Nonwoven polyester and nonwoven polypropylene (craft fabrics, medical masks, and medical wraps) showed higher quality factors than woven materials (flannel cotton, Kona cotton, sateen cotton). Materials with meltblown nonwoven polypropylene filtered best, especially against submicron particles. Subsequently, we combined high performing fabrics into multi-layer sets, evaluating the sets’ quality factors before and after our washing protocol, which included machine washing, machine drying, and isopropanol soak. Sets incorporating meltblown nonwoven polypropylene designed for filtration degraded significantly post-wash in the submicron range where they excelled prior to washing (Q > 50 kPa-1 at 1 μm, respectively, degraded to Q < 10 post-wash). Washing caused lesser quality degradation in sets incorporating spunbond non-woven polypropylene or medical wraps (Q = 12 to 24 pre-wash, Q = 8 to 10 post-wash). Post-wash quality factors are similar for all multi-layer sets in this study, and higher than Kona quilting cotton (Q = 6). Washed multi-layer sets filtered 12% to 42% of 0.5 μm, 27% to 76% of 1 μm, 58% to 96% of 2.8 μm, and 72% to 100% of 4.2 μm. The measured filtration and pressure drop of both the homogeneous and heterogeneous multi-layer fabric combinations agreed with the estimations from a model assuming layers filter independently. Further examination of selective nonwovens showed that IPA degraded their filtration, while washing and drying produced variable effects on their filtration. Variability in filtration and pressure drop was observed in and across Filti samples.

Air pollution and recurrence of cardiovascular events after ST-segment elevation myocardial infarction

Background and aimsThe effects of air pollution on discharged patients after ST-segment elevation myocardial infarction (STEMI) still remain uncertain. We examined the association between air pollutants and recurrent cardiovascular events in STEMI survivors. MethodsA retrospective cohort of 1641 discharged patients after STEMI was established in 2013 and followed until the end of 2019. Concentrations of air pollutants including fine particles <2.5 μm aerodynamic diameter (PM2.5), inhalable particles <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 exposure assessment. Multivariate-adjusted Cox proportional hazards models were used to estimate the increased risks of recurrent cardiovascular events. ResultsCompared with the first exposure quartile, for short-term exposure, hazard ratios (HRs) of recurrent cardiovascular events associated with the fourth exposure quartiles of PM2.5, PM10, NO2, SO2, CO, and O3 were 4.06 (95% CI: 2.62–6.30), 3.79 (95% CI: 2.57–5.58), 2.22 (95% CI: 1.67–2.94), 4.47 (95% CI: 3.08–6.48), 3.73 (95% CI: 2.54–5.48), and 5.35 (95% CI: 3.12–9.20), respectively. For long-term exposure, HRs associated with the fourth exposure quartiles of PM2.5, PM10, NO2, SO2, CO, and O3 were 6.43 (95% CI: 3.60–11.47), 4.77 (95% CI: 2.85–7.99), 3.22 (95% CI: 2.00–5.19), 3.20 (95% CI: 2.05–5.01), 4.44 (95% CI: 2.65–7.45), and 1.07 (95% CI: 0.80–1.42), respectively. The risks of recurrent cardiovascular events brought by air pollutants mostly increased nonlinearly. ConclusionsShort- and long-term exposure to air pollutants except ozone increases the risks of recurrent cardiovascular events in STEMI survivors. Better environmental policies and secondary prevention strategies should be developed to protect STEMI survivors as a susceptible population.

Spatial and Temporal Variations in PM10 Concentrations between 2010-2017 in South Africa.

Particulate matter less than or equal to 10 μm in aerodynamic diameter (PM10 µg/m3) is a priority air pollutant and one of the most widely monitored ambient air pollutants in South Africa. This study analyzed PM10 from monitoring 44 sites across four provinces of South Africa (Gauteng, Mpumalanga, Western Cape and KwaZulu-Natal) and aimed to present spatial and temporal variation in the PM10 concentration across the provinces. In addition, potential influencing factors of PM10 variations around the three site categories (Residential, Industrial and Traffic) were explored. The spatial trend in daily PM10 concentration variation shows PM10 concentration can be 5.7 times higher than the revised 2021 World Health Organization annual PM10 air quality guideline of 15 µg/m3 in Gauteng province during the winter season. Temporally, the highest weekly PM10 concentrations of 51.4 µg/m3, 46.8 µg/m3, 29.1 µg/m3 and 25.1 µg/m3 at Gauteng, Mpumalanga, KwaZulu-Natal and Western Cape Province were recorded during the weekdays. The study results suggest a decrease in the change of annual PM10 levels at sites in Gauteng and Mpumalanga Provinces. An increased change in annual PM10 levels was reported at most sites in Western Cape and KwaZulu-Natal.

Soil loss and PM10 emissions from agricultural fields in the Junggar Basin over the past six decades

The Junggar Basin in north Xinjiang Province is regarded as one of the important dust sources in China. There is, however, a lack of information on long-term dust emissions originating from the basin. In these largely agricultural communities, wind erosion is a major concern that results in a threat to sustainable agriculture and environmental quality. This study assesses dust emissions from the agricultural community of the Junggar Basin in north Xinjiang based on soil and land use types extracted from remote sensing data in response to weather and climate over the past six decades. The Wind Erosion Prediction System (WEPS) was used to simulate annual soil loss and PM10 (particulate matter ≤10 μm in aerodynamic diameter) emissions at 11 meteorological stations across the Junggar Basin. From 1958 to 2018, annual soil loss and PM10 emissions significantly decreased 3.65 and 0.2 kg m^–2 y^–1, respectively. This decrease was likely due to decreasing wind speed, but also associated with increased precipitation and temperature, and decreased solar radiation. Wind erosion occurred most frequently during April and May, accounting for 39% of the annual soil loss and 40% of the annual PM10 emission. In contrast, no erosion occurred in January, February, and December as a result of low temperature (&lt;–8.6°C), frozen soil conditions, and snow cover. Wind erosion risk appeared to decrease during the past six decades in response to observed climate change across the basin; however the southeast part of the basin experienced increasing wind erosion risk over the six decades. Projects to control wind erosion risk and combat dust emission should be given priority in the southeast part of the basin. Frequency of dust events was compared to simulated erosion; a strong linkage was found between simulated soil loss and frequency of dust storms based on regression analysis. This demonstrated that the modelling was acceptable in the conditions of this study and the results were prone to be reliable.

Long-Term Air Pollution Exposure and COVID-19 Mortality: A Patient-Level Analysis from New York City.

Rationale: Risk factors for coronavirus disease (COVID-19) mortality may include environmental exposures such as air pollution. Objectives: To determine whether, among adults hospitalized with PCR-confirmed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), long-term air pollution exposure is associated with the risk of mortality, ICU admission, or intubation. Methods: We performed a retrospective analysis of SARS-CoV-2 PCR-positive patients admitted to seven New York City hospitals from March 8, 2020, to August 30, 2020. The primary outcome was mortality; secondary outcomes were ICU admission and intubation. We estimated the annual average fine particulate matter (particulate matter ⩽2.5 μm in aerodynamic diameter [PM2.5]), nitrogen dioxide (NO2), and black carbon (BC) concentrations at patients' residential address. We employed double robust Poisson regression to analyze associations between the annual average PM2.5, NO2, and BC exposure level and COVID-19 outcomes, adjusting for age, sex, race or ethnicity, hospital, insurance, and the time from the onset of the pandemic. Results: Among the 6,542 patients, 41% were female and the median age was 65 (interquartile range, 53-77) years. Over 50% self-identified as a person of color (n = 1,687 [26%] Hispanic patients; n = 1,659 [25%] Black patients). Air pollution exposure levels were generally low. Overall, 31% (n = 2,044) of the cohort died, 19% (n = 1,237) were admitted to the ICU, and 16% (n = 1,051) were intubated. In multivariable models, a higher level of long-term exposure to PM2.5 was associated with an increased risk of mortality (risk ratio, 1.11 [95% confidence interval, 1.02-1.21] per 1-μg/m3 increase in PM2.5) and ICU admission (risk ratio, 1.13 [95% confidence interval, 1.00-1.28] per 1-μg/m3 increase in PM2.5). In multivariable models, neither NO2 nor BC exposure was associated with COVID-19 mortality, ICU admission, or intubation. Conclusions: Among patients hospitalized with COVID-19, a higher long-term PM2.5 exposure level was associated with an increased risk of mortality and ICU admission.

Invited Perspective: Moving from Characterizing to Addressing Racial/Ethnic Disparities in Air Pollution Exposure.

Invited Perspective: Moving from Characterizing to Addressing Racial/Ethnic Disparities in Air Pollution Exposure.

Evidence of free tropospheric and long-range transport of microplastic at Pic du Midi Observatory

The emerging threat of atmospheric microplastic pollution has prompted researchers to study areas previously considered beyond the reach of plastic. Investigating the range of atmospheric microplastic transport is key to understanding the global extent of this problem. While atmospheric microplastics have been discovered in the planetary boundary layer, their occurrence in the free troposphere is relatively unexplored. Confronting this is important because their presence in the free troposphere would facilitate transport over greater distances and thus the potential to reach more distal and remote parts of the planet. Here we show evidence of 0.09–0.66 microplastics particles/m3 over 4 summer months from the Pic du Midi Observatory at 2877 meters above sea level. These results exhibit true free tropospheric transport of microplastic, and high altitude microplastic particles <50 µm (aerodynamic diameter). Analysis of air/particle history modelling shows intercontinental and trans-oceanic transport of microplastics illustrating the potential for global aerosol microplastic transport.