Fine Particulate Air Research Articles

The Environmental Burden of the United States' Bitcoin Mining Boom.

Bitcoin mines-massive computing clusters generating cryptocurrency tokens-consume vast amounts of electricity. The amount of fine particle (PM2.5) air pollution created because of their electricity consumption, and its effect on environmental health, is unknown. In this study, we located the 34 largest mines in the United States in 2022, identified the electricity-generating plants that responded to them, and pinpointed communities most harmed by Bitcoin mine-attributable air pollution. From mid-2022 to mid-2023, the 34 mines consumed 32.3 terawatt-hours of electricity-33% more than Los Angeles-85% of which came from fossil fuels. We estimated that 1.9 million Americans were exposed to ≥0.1 μg/m3 of additional PM2.5 pollution from Bitcoin mines, which were often hundreds of miles away from communities they affected. Americans living in four regions-including New York City and near Houston-were exposed to the highest Bitcoin mine-attributable PM2.5 concentrations (≥0.5 μg/m3) with the greatest health risks.

Features of the chemical composition of fine suspended particles in the atmospheric air of residential and industrial zones of the city of Sibay, Republic of Bashkortostan

Introduction. Atmospheric particulate matter as a negative environmental factor can be a significant hazard depending on their size, morphometric and physicochemical characteristics. The purpose of the study. To investigate the elemental composition of finely dispersed suspended particles in the atmospheric air of the industrial zones of the mining center of the Bashkir Trans-Urals - the city of Sibay. Materials and methods. Air sampling was carried out in the industrial area of ​​Sibay using an AVA-3-240/180-01 automatic three-channel air aspirator with AFA-VP-20 filters. Microscopy of samples and determination of the elemental composition of dust emissions were carried out at the Interdisciplinary Center “Analytical Microscopy” of the Kazan Federal University (Kazan) on a universal analytical complex for scanning field emission electron microscopy Merlin (Carl Zeiss). Results. On electron micrographs, there were identified particles of various sizes, mostly round in shape with clear edges, located solitary. In the automatic mode of processing the spectra, the peaks of the elements in the spectrum were automatically recognized and identified. In addition to carbon and oxygen, the calcium, iron, silicon, potassium, aluminium, copper, sulphur, sodium and magnesium are main chemical constituents of particulate matter encountered at all sampling points. Zinc was present in dust samples at three points, scandium, titanium, cobalt, barium, and manganese – only at one point. The possibility of the relation between the content of fine particles in the air and the increased incidence of cardiovascular, bronchopulmonary diseases, including asthma, in the population of Sibay is discussed. Limitations. The study of the elemental composition of fine dust in the city of Sibay was carried out using atmospheric air samples taken at 5 points located in residential and industrial areas. Conclusion. The increased content of fine particles in the atmospheric air of the city of Sibay increases the risks of respiratory and cardiovascular diseases, as well as other health abnormalities, in the population permanently residing near industrial zones. The obtained data on the parameters of dust particles are the basis for assessing the share contribution of industrial enterprises to air pollution and making management decisions to improve the environmental situation in the industrial center of the mining region.

Constituents of fine particle air pollution and oxidative stress, quality of life of patient with allergic rhinitis: A panel study

Constituents of fine particle air pollution and oxidative stress, quality of life of patient with allergic rhinitis: A panel study

Monitoring and Control of Particulate Matter in Urban Area in Douala-Cameroon Town

This study focused on the content of fine particle air pollution in the city of Douala. Several studies have analyzed pollution problems due to road traffic in Douala, Cameroon. Particle concentration levels are higher in heavy traffic than in light traffic. The population’s exposure to air pollution in cities is higher near roads. Several studies have analyzed pollution problems due to road traffic in Douala, Cameroon. In this city, the traffic density at the intersections is indeed higher. Thus, the question is as follows: Are these traffic areas hotspots of increased PM exposure levels? To determine it, four particle size fractions (PM10, PM2.5, PM5, and PM1) were collected using an “OC300 Gas and Dust Particle Laser Detector” for three months at different traffic locations (roundabouts or/and crossroads). Statistical analysis of the data shows very high concentrations at most measurement sites. PM concentrations at the different measurement sites are around 35.69-68.08 µg m−3 for PM1, 50.72-99.13 µg m−3 for PM2.5, 54.11-111.22 µg m−3 for PM5, and 57.97-119.25 µg m−3 for PM10. Exceedances of WHO daily guidelines for PM2.5 (45 µg m−3) and PM10 (15 µg m−3) were found during the measurement campaign, indicating that crossroads are the pollution hotspots in urban areas. Occupation of the roadsides for various economic activities (painting, restaurants, donut shops, etc.) is common in Cameroon, increasing health risks for people working around the roadside. Thus, crossroad locations are areas where the level of exposure to PMx is the highest on road traffics.

Fine particle air pollution and lung cancer risk: Extending the long list of health risks

Exposures to fine particulate matter (PM2.5) concentrations above the WHO guidelines affect 99% of the world population. In a recent issue of Nature, Hill etal. dissect the tumor promotion paradigm orchestrated by PM2.5 inhalation exposures in lung carcinogenesis, supporting the hypothesis that PM2.5 can increase your risk of lung carcinoma without ever smoking.

Quantifying Risk to Flight Attendants from Secondhand Smoke Exposure in Airline Cabins Using Pharmacokinetic Modeling: A Case Report

Background: Several studies of the health problems incurred by flight attendants flying during the smoking years concluded that they suffered elevated rates of chronic bronchitis, heart disease, skin cancer, breast cancer, melanoma, reproductive cancers, middle ear infections, hearing loss, asthma, pneumonia, chronic obstructive pulmonary disease, various pulmonary function abnormalities, plus depression and anxiety. Aims: Systematic review of secondhand smoke risks to flight attendants, exemplified using a specific case involving a deceased flight attendant who suffered from a multiplicity of tobacco-smoke-related diseases, including asthma, breast cancer, carotid artery stenosis, cataracts, cervical cancer, chronic obstructive pulmonary disease, coronary artery disease, laryngeal cancer, pneumonia and chronic myeloid leukemia. The decedent died in 2014 at age 68, losing an estimated 18.5 years of life expectancy. Methods: Pharmacokinetic modeling was used for the first time to estimate the risk from secondhand smoke for flight attendants on typical passenger aircraft flown by the decedent during an 18 year period ending in 1988. Results: Based on in-flight cotinine dosimetry measured in an Air Canada study, typical flight attendants would have inhaled a dose-equivalent of fine particle air pollution exceeding the “Air Pollution Emergency” levels of the U.S. Environmental Protection Agency’s Air Quality Index. The secondhand smoke cotinine dose for typical flight attendants in aircraft cabins is estimated to have been 6-fold that of the average US worker and 14-fold that of the average person. Thus, ventilation systems massively failed to control secondhand smoke air pollution in aircraft cabins, and led to extreme exposures. The decedent’s estimated lifetime cancer risk from secondhand smoke was 18 times U.S. OSHA’s Significant Risk of Material Impairment of Health level of 1 per 1000 per working lifetime. Conclusions: In-flight exposure to toxic and carcinogenic tobacco smoke in smoky passenger cabins was the major risk factor leading to the decedent’s multiple smoking-related diseases, and her premature death. This has implications for the extant and future health of the cohort of surviving flight attendants exposed to secondhand smoke on aircraft during the 20th Century Era.

Single-Particle Metal Fingerprint Analysis and Machine Learning Pipeline for Source Apportionment of Metal-Containing Fine Particles in Air

Single-Particle Metal Fingerprint Analysis and Machine Learning Pipeline for Source Apportionment of Metal-Containing Fine Particles in Air

Incident Dementia and Long‐Term Exposure to Constituents of U.S. Fine Particle Air Pollution: A National Cohort Study

AbstractBackgroundGrowing evidence suggests that PM2.5 likely increases the risks of neurological disorders, yet little is known about the relative contributions of different constituents. Understanding constituent‐specific effects are critical to targeting emission reductions of specific sources with the greatest health protection.MethodWe conducted a nationwide population‐based cohort study (2000‐2017), by integrating the Medicare Chronic Conditions Warehouse database and two sets of high‐resolution, multiple‐species, air pollution datasets to investigate the impact of long‐term exposure to PM2.5 constituents on incident dementia and Alzheimer’s disease (AD). and home health‐care claims. Hazard ratios for dementia and AD were estimated using single‐ and multi‐constituent Cox proportional hazards models, and penalized splines were used to evaluate potential nonlinear concentration‐response relationships.ResultsOf the 18.5 million dementia and 19.2 million AD individuals within these cohorts, 31.5% and 14.6% developed dementia and AD events, respectively. From the single‐pollutant models, an interquartile range (IQR) increase in PM2.5 mass was associated with an increase in dementia incidence ranging between 6‐7% using two exposure datasets. For different PM2.5 constituents, associations remained significant in black carbon (BC), organic matter (OM), sulfate (SO4 2−), and ammonium (NH4 +). Incident dementia was observed to have the strongest association with increases in exposure to SO4 2− and BC (10‐11% increase and 4‐6% per IQR increase, respectively). Effect estimates for AD were even larger. For both endpoints, all constituents had largely linear concentration‐response relationships in the low exposure range, but most tailed off at high exposure concentrations, particularly for AD.ConclusionOur study suggests that long‐term exposure to PM2.5 is significantly associated with increased incident dementia and AD, and that the different PM2.5 constituents may elicit differential neurotoxicity. Reduction of PM2.5 emissions, especially for the main sources of BC and SO4 2−, may reduce the burden of dementia or AD in the aging US population.

Incident Dementia and Long-Term Exposure to Constituents of U.S. Fine Particle Air Pollution: A National Cohort Study

Incident Dementia and Long-Term Exposure to Constituents of U.S. Fine Particle Air Pollution: A National Cohort Study

Perinatal Health Inequalities in the Industrial Region of Estonia: A Birth Registry-Based Study.

Despite the increasing number of studies on industrially contaminated sites (ICS) and their health effects, there are very few studies on perinatal health outcomes in ICSs. In the present study, we examined the perinatal health inequalities by comparing adverse birth outcomes (ABOs) in the oil shale industry region of Ida-Viru County in Estonia with national-level figures and investigated the effects of maternal environmental and sociodemographic factors. Based on the 208,313 birth records from 2004–2018, Ida-Viru ICS has a birth weight 124.5 g lower than the average of 3544 g in Estonia. A higher prevalence of preterm birth (4.3%) and low birth weight (4.8%) in Ida-Viru ICS is found compared to 3.3% on both indicators at the national level. Multiple logistic regression analysis shows the statistically significant association of ABOs with fine particle (PM2.5) air pollution, mother’s ethnicity, and education throughout Estonia. However, in Ida-Viru ICS, the ABOs odds are remarkably higher in these characteristics except for the mother’s ethnicity. Furthermore, the ABOs are associated with the residential proximity to ICS. Thus, the Ida-Viru ICS has unequally higher odds of adverse perinatal health across the environmental and sociodemographic factors. In addition to reducing the air pollutants, policy actions on social disparities are vital to address the country’s unjustly higher perinatal health inequalities, especially in the Ida-Viru ICS.

Prediction Tool on Fine Particle Pollutants and Air Quality for Environmental Engineering.

This article focuses on the research, design and implementation of a prediction tool for air quality to estimate pollutant concentrations, contributing to environmental engineering. It addresses prediction of fine particle air pollutants of diameter less than 2.5 µm (particulate matter 2.5), their concentration being substantially influenced by urban traffic. We collect worldwide multicity data from health-related public sources on which mining is performed using classical data mining/machine learning paradigms: association rules, clustering and classification. Challenges include adapting appropriate techniques based on data, and capturing subtle domain-specific aspects. The prediction tool is built using knowledge discovered by mining, leveraging health standards, catering to novice, intermediate and expert users. The prediction output is accurate, efficient, interpretable and useful as evident from our experiments. The tool is helpful for urban decision support. This work is beneficial in developing software systems such as intelligent tutors, mobile device apps and smart city tools. It contributes to smart environment, mobility and living, making a positive impact on smart cities and sustainability. In this work, we claim that classical computational paradigms in their fundamental form can be adapted to solve environmental engineering problems, with easy comprehension, as per the Occam’s razor principle that advocates simplicity. This article constitutes applied research: using computational techniques to solve domain-specific problems. Future work includes exploring models in deep learning such as CNN and Bi-LSTM, and considering different types of pollutants as well as other sources besides multicity traffic data, to conduct further studies. This would address additional challenges with enhancements.

Abstract 11282: Meta-Analysis of Residential Portable Air Cleaner Use and Circulating Inflammatory Biomarkers

Introduction: Fine particulate matter air pollution (PM 2.5 ) exposure is associated with elevated circulating inflammatory biomarkers implicated in cardiovascular disease (CVD). Portable Air Cleaners (PAC)s reduce PM 2.5 exposure and may lower concentrations of inflammatory biomarkers. Methods: We performed a systematic review and meta-analysis of randomized crossover trials of in-home high efficiency particulate air (HEPA) PACs vs. sham control on changes in CRP, IL-6, and/or TNFα among adults with no smoking exposure using Medline, Embase, and Cochrane Central Register of Controlled Trials with the Ovid Platform, Inspec, Compendix, and Web of Science Core Collection. Two investigators (S.W, D.W.) independently screened and reviewed the studies. We used RevMan 5.3 to perform the meta-analysis. Results: Search results included 459 articles screened, 26 selected for full review, and 14 that met inclusion criteria, representing N=724 participants included in the meta-analysis. Ten studies reported CRP, 9 reported IL-6, and 5 reported TNFα. Based on WHO guidelines, 5 studies were in regions of extreme PM 2.5 exposure (>35 μg/m 3 ), 3 were high (10-35 μg/m 3 ), 3 were low (<10 μg/m 3 ), and 2 lacked baseline PM 2.5 . Median (± S.D.) duration of HEPA/sham use was 9 ± 6.6 days. Reductions in PM 2.5 ranged from 2.6 to 54.9 μg/m 3 (35-82%) and varied by baseline PM 2.5 , although reporting of baseline PM 2.5 was incomplete across trials. Compared to sham PAC use, active PACs were associated with a 7% lower CRP (95% CI -13%, 0%) and 12% lower IL-6 (-22%, -2%), P<0.05 for both (Figure). Subgroup analyses demonstrated consistency of effect of PACs across levels of baseline PM 2.5 . Conclusions: Our data demonstrate that PAC use is associated with significant reductions in circulating CRP and IL-6, with a magnitude of effect similar to clinical trials of statins and IL-1β inhibition. Given the role of inflammation in CVD, PACs may be useful to reduce systemic inflammation and cardiovascular risk.

Electrostatic Charge Retention in PVDF Nanofiber-Nylon Mesh Multilayer Structure for Effective Fine Particulate Matter Filtration for Face Masks.

Currently, almost 70% of the world’s population occupies urban areas. Owing to the high population density in these regions, they are exposed to various types of air pollutants. Fine particle air pollutants (<2.5 μm) can easily invade the human respiratory system, causing health issues. For fine particulate matter filtration, the use of a face mask filter is efficient; however, its use is accompanied by a high-pressure drop, making breathing difficult. Electrostatic interactions in the filter of the face mask constitute the dominant filtration mechanism for capturing fine particulate matter; these masks are, however, significantly weakened by the high humidity in exhaled breath. In this study, we demonstrate that a filter with an electrostatically rechargeable structure operates with normal breathing air power. In our novel face mask, a filter membrane is assembled by layer-by-layer stacking of the electrospun PVDF nanofiber mat formed on a nylon mesh. Tribo/piezoelectric characteristics via multilayer structure enhance filtration performance, even under air-powered filter bending taken as a normal breathing condition. The air gap between nanofiber and mesh layers increases air diffusion time and preserves the electrostatic charges within the multi-layered nanofiber filter membrane under humid air penetration, which is advantageous for face mask applications.

Invited Perspective: Air Pollution and Dementia: Challenges and Opportunities.

Invited Perspective: Air Pollution and Dementia: Challenges and Opportunities.

The trends in quality changes of the Sofia atmospheric air for a 12-year period

The official data of the Executive Environment Agency (ExEA) for the contents of SO2, NO2, fine air particles, O3, CO and C6H6 in the atmospheric air on the territory of Sofia for a 12-year period (2007 – 2018) are analyzed. The trends in their seasonal and annual changes defining the air quality in the urban environment are outlined.

Within-City Variation in Reactive Oxygen Species from Fine Particle Air Pollution and COVID-19

Rationale: Evidence linking outdoor air pollution with coronavirus disease (COVID-19) incidence and mortality is largely based on ecological comparisons between regions that may differ in factors such as access to testing and control measures that may not be independent of air pollution concentrations. Moreover, studies have yet to focus on key mechanisms of air pollution toxicity such as oxidative stress.Objectives: To conduct a within-city analysis of spatial variations in COVID-19 incidence and the estimated generation of reactive oxygen species (ROS) in lung lining fluid attributable to fine particulate matter (particulate matter with an aerodynamic diameter ⩽2.5 μm [PM2.5]).Methods: Sporadic and outbreak-related COVID-19 case counts, testing data, population data, and sociodemographic data for 140 neighborhoods were obtained from the City of Toronto. ROS estimates were based on a mathematical model of ROS generation in lung lining fluid in response to iron and copper in PM2.5. Spatial variations in long-term average ROS were predicted using a land-use regression model derived from measurements of iron and copper in PM2.5. Data were analyzed using negative binomial regression models adjusting for covariates identified using a directed acyclic graph and accounting for spatial autocorrelation.Measurements and Main Results: A significant positive association was observed between neighborhood-level ROS and COVID-19 incidence (incidence rate ratio = 1.07; 95% confidence interval, 1.01–1.15 per interquartile range ROS). Effect modification by neighborhood-level measures of racialized group membership and socioeconomic status was also identified.Conclusions: Examination of neighborhood characteristics associated with COVID-19 incidence can identify inequalities and generate hypotheses for future studies.

Suspension of Fine Particles in Air and their Removal by Ventilation in an Indoor Environment as a Model of a Pharmaceutical Manufacturing Facility

Suspension of Fine Particles in Air and their Removal by Ventilation in an Indoor Environment as a Model of a Pharmaceutical Manufacturing Facility

The Behavior of Microdroplets By the Acoustic Wave Interference

The microdroplet in the air have been recently issued in the view of environmental pollution and infectious virus. The microdroplet with fine dust have been challenged to solve with conventional techniques such as filtering, electrostatic, etc. We investigated the novel technology for decreasing the fine particles in air induced by sound wave with the frequency ranging from 20Hz to 20kHz and the sound pressure level (SPL) from 0 to 100dB.The test systems in our study were set up with constraint box, sound wave actuator, ultra-fine particle distributor, particle counter, decibel meter, etc. the variation of density of ultra-fine particles from distributor was characterized with operating time of sound wave, and compared with the density as no operating.When the low frequency and the SPL under 50Hz and 100dB were applied in the constraint box containing ultra-fine particles, the rate of decrease of ultra-fine particles in density was nearly 5 times higher than that without operating. And it can be applied to increase the efficiency of the conventional particle collection technology such as the commercial filter.It is concluded that the behavior of microdroplets was effectively analyzed by the acoustic wave interference, and also is expected to be applied to the various fields

Personal-Level Protective Actions Against Particulate Matter Air Pollution Exposure: A Scientific Statement From the American Heart Association.

Since the publication of the last American Heart Association scientific statement on air pollution and cardiovascular disease in 2010, unequivocal evidence of the causal role of fine particulate matter air pollution (PM2.5, or particulate matter ≤2.5 μm in diameter) in cardiovascular disease has emerged. There is a compelling case to provide the public with practical personalized approaches to reduce the health effects of PM2.5. Such interventions would be applicable not only to individuals in heavily polluted countries, high-risk or susceptible individuals living in cleaner environments, and microenvironments with higher pollution exposures, but also to those traveling to locations with high levels of PM2.5. The overarching motivation for this document is to summarize the current evidence supporting personal-level strategies to prevent the adverse cardiovascular effects of PM2.5, guide the use of the most proven/viable approaches, obviate the use of ineffective measures, and avoid unwarranted interventions. The significance of this statement relates not only to the global importance of PM2.5, but also to its focus on the most tested interventions and viable approaches directed at particulate matter air pollution. The writing group sought to provide expert consensus opinions on personal-level measures recognizing the current uncertainty and limited evidence base for many interventions. In doing so, the writing group acknowledges that its intent is to assist other agencies charged with protecting public health, without minimizing the personal choice considerations of an individual who may decide to use these interventions in the face of ongoing air pollution exposure.

Neurodegenerative hospital admissions and long-term exposure to ambient fine particle air pollution

PurposeLong-term exposure to ambient fine particle (PM2.5) concentrations has been associated with an increased rate or risk of neurodegenerative conditions, but individual PM sources have not been previously examined in relation to neurodegenerative diseases. MethodsUsing the Statewide Planning and Research Cooperative System database, we studied 63,287 hospital admissions with a primary diagnosis of either Alzheimer's disease, dementia, or Parkinson's disease for New York State residents living within 15 miles from six PM2.5 monitoring sites. In addition to PM2.5 concentrations, we studied seven specific PM2.5 sources: secondary sulfate, secondary nitrate, biomass burning, diesel, spark-ignition emissions, pyrolyzed organic rich, and road dust. We estimated the rate of neurodegenerative hospital admissions associated with increased concentration of PM2.5 and individual PM2.5 sources average concentrations in the previous 0–29, 0–179, and 0–364 days. ResultsIncreases in ambient PM2.5 concentrations were not consistently associated with increased hospital admissions rates. Increased source-specific PM2.5 concentrations were associated with both increased (e.g., secondary sulfates and diesel emissions) and decreased rates (e.g., secondary nitrate and spark-ignition vehicular emissions) of neurodegenerative admissions. ConclusionsWe did not observe clear associations between overall ambient PM2.5 concentrations or source-apportioned ambient PM2.5 contributions and rates of neurologic disease hospitalizations.