scholarly journals The Relationship between Fossil Fuel Utilization and Ambient Air Fine Particulate Matter

2002 ◽  
Vol 16 (2) ◽  
pp. 221-221 ◽  
Author(s):  
Curt M. White ◽  
Richard R. Anderson ◽  
Donald V. Martello
Keyword(s):  
Particulate Matter ◽  
Fossil Fuel ◽  
Fine Particulate Matter ◽  
Ambient Air ◽  
Fuel Utilization ◽  
Fine Particulate ◽  
The Relationship

scholarly journals The Relationship between Daily Concentration of Fine Particulate Matter in Ambient Air and Exacerbation of Respiratory Diseases in Silesian Agglomeration, Poland

2019 ◽  
Vol 16 (7) ◽  
pp. 1131 ◽  
Author(s):  
Małgorzata Kowalska ◽  
Michał Skrzypek ◽  
Michał Kowalski ◽  
Josef Cyrys ◽  
Niewiadomska Ewa ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Respiratory Diseases ◽  
Moving Average ◽  
Fine Particulate Matter ◽  
Ambient Air ◽  
Average Concentration ◽  
Outpatient Visits ◽  
Fine Particulate ◽  
Daily Concentration ◽  
The Relationship

The relationship between the worsening of air quality during the colder season of the year and respiratory health problems among the exposed population in many countries located in cold climates has been well documented in numerous studies. Silesian Voivodeship, a region located in southern Poland, is one of the most polluted regions in Europe. The aim of this study was to assess the relationship between daily concentration of particulate matter (PM: PM2.5 and PM10) in ambient air and exacerbations of respiratory diseases during the period from 1 January 2016 to 31 August 2017 in the central agglomeration area of Silesian Voivodeship. The study results confirmed a significant increase of daily fine particulate matter concentration in ambient air during the cold season in Silesian Voivodeship with a simultaneous increase of the number of outpatient visits and hospitalizations due to respiratory diseases. The moving average concentration was better suited for the modelling of biological response as a result of PM2.5 or PM10 exposure than the temporal lag of health effects. Each increase of dose expressed in the form of moving average concentration over a longer time leads to an increase in the daily number of respiratory effects. The highest risk of hospitalization due to respiratory diseases was related to longer exposure of PM expressed by two to four weeks of exposure; outpatient visits was related to a shorter exposure duration of 3 days.

scholarly journals Effect of Short-Term Exposure to Fine Particulate Matter and Temperature on Acute Myocardial Infarction in Korea

2021 ◽  
Vol 18 (9) ◽  
pp. 4822
Author(s):  
Jiyoung Shin ◽  
Jongmin Oh ◽  
In Sook Kang ◽  
Eunhee Ha ◽  
Wook Bum Pyun
Keyword(s):  
Myocardial Infarction ◽  
Acute Myocardial Infarction ◽  
Particulate Matter ◽  
Fine Particulate Matter ◽  
Ambient Air ◽  
Cold Season ◽  
Short Term ◽  
Fine Particulate ◽  
Short Term Exposure ◽  
The Impact

Background/Aim: Previous studies have suggested that the short-term ambient air pollution and temperature are associated with myocardial infarction. In this study, we aimed to conduct a time-series analysis to assess the impact of fine particulate matter (PM2.5) and temperature on acute myocardial infarction (AMI) among adults over 20 years of age in Korea by using the data from the Korean National Health Information Database (KNHID). Methods: The daily data of 192,567 AMI cases in Seoul were collected from the nationwide, population-based KNHID from 2005 to 2014. The monitoring data of ambient PM2.5 from the Seoul Research Institute of Public Health and Environment were also collected. A generalized additive model (GAM) that allowed for a quasi-Poisson distribution was used to analyze the effects of PM2.5 and temperature on the incidence of AMI. Results: The models with PM2.5 lag structures of lag 0 and 2-day averages of lag 0 and 1 (lag 01) showed significant associations with AMI (Relative risk [RR]: 1.011, CI: 1.003–1.020 for lag 0, RR: 1.010, CI: 1.000–1.020 for lag 01) after adjusting the covariates. Stratification analysis conducted in the cold season (October–April) and the warm season (May–September) showed a significant lag 0 effect for AMI cases in the cold season only. Conclusions: In conclusion, acute exposure to PM2.5 was significantly associated with AMI morbidity at lag 0 in Seoul, Korea. This increased risk was also observed at low temperatures.

The relationship between fine particulate matter (PM2.5) and schizophrenia severity

2018 ◽  
Vol 91 (5) ◽  
pp. 613-622 ◽  
Author(s):  
Rika Eguchi ◽  
Daisuke Onozuka ◽  
Kouji Ikeda ◽  
Kenji Kuroda ◽  
Ichiro Ieiri ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Fine Particulate Matter ◽  
Fine Particulate ◽  
The Relationship

scholarly journals On the contribution of nocturnal heterogeneous reactive nitrogen chemistry to particulate matter formation during wintertime pollution events in Northern Utah

2019 ◽  
Vol 19 (14) ◽  
pp. 9287-9308 ◽  
Author(s):  
Erin E. McDuffie ◽  
Caroline C. Womack ◽  
Dorothy L. Fibiger ◽  
William P. Dube ◽  
Alessandro Franchin ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Salt Lake ◽  
Fine Particulate Matter ◽  
Ambient Air ◽  
Atmospheric Conditions ◽  
Mixing Processes ◽  
Salt Lake Valley ◽  
Fine Particulate ◽  
Northern Utah ◽  
Pollution Events

Abstract. Mountain basins in Northern Utah, including the Salt Lake Valley (SLV), suffer from wintertime air pollution events associated with stagnant atmospheric conditions. During these events, fine particulate matter concentrations (PM2.5) can exceed national ambient air quality standards. Previous studies in the SLV have found that PM2.5 is primarily composed of ammonium nitrate (NH4NO3), formed from the condensation of gas-phase ammonia (NH3) and nitric acid (HNO3). Additional studies in several western basins, including the SLV, have suggested that production of HNO3 from nocturnal heterogeneous N2O5 uptake is the dominant source of NH4NO3 during winter. The rate of this process, however, remains poorly quantified, in part due to limited vertical measurements above the surface, where this chemistry is most active. The 2017 Utah Winter Fine Particulate Study (UWFPS) provided the first aircraft measurements of detailed chemical composition during wintertime pollution events in the SLV. Coupled with ground-based observations, analyses of day- and nighttime research flights confirm that PM2.5 during wintertime pollution events is principally composed of NH4NO3, limited by HNO3. Here, observations and box model analyses assess the contribution of N2O5 uptake to nitrate aerosol during pollution events using the NO3- production rate, N2O5 heterogeneous uptake coefficient (γ(N2O5)), and production yield of ClNO2 (φ(ClNO2)), which had medians of 1.6 µg m−3 h−1, 0.076, and 0.220, respectively. While fit values of γ(N2O5) may be biased high by a potential under-measurement in aerosol surface area, other fit quantities are unaffected. Lastly, additional model simulations suggest nocturnal N2O5 uptake produces between 2.4 and 3.9 µg m−3 of nitrate per day when considering the possible effects of dilution. This nocturnal production is sufficient to account for 52 %–85 % of the daily observed surface-level buildup of aerosol nitrate, though accurate quantification is dependent on modeled dilution, mixing processes, and photochemistry.

scholarly journals Low levels of fine particulate matter increase vascular damage and reduce pulmonary function in young healthy adults

2020 ◽  
Vol 17 (1) ◽  
Author(s):  
Lauren H. Wyatt ◽  
Robert B. Devlin ◽  
Ana G. Rappold ◽  
Martin W. Case ◽  
David Diaz-Sanchez
Keyword(s):  
Particulate Matter ◽  
Pulmonary Function ◽  
Adhesion Molecule ◽  
Human Exposure ◽  
Fine Particulate Matter ◽  
Ambient Air ◽  
P Wave ◽  
Low Level ◽  
Link Type ◽  
Fine Particulate

Abstract Background Fine particulate matter (PM2.5) related mild inflammation, altered autonomic control of cardiovascular function, and changes to cell function have been observed in controlled human exposure studies. Methods To measure the systemic and cardiopulmonary impacts of low-level PM exposure, we exposed 20 healthy, young volunteers to PM2.5, in the form of concentrated ambient particles (mean: 37.8 μg/m3, SD 6.5), and filtered air (mean: 2.1 μg/m3, SD 2.6). In this double-blind, crossover study the exposure order was randomized. During the 4 h exposure, volunteers (7 females and 13 males) underwent light intensity exercise to regulate ventilation rate. We measured pulmonary, cardiac, and hematologic end points before exposure, 1 h after exposure, and again 20 h after exposure. Results Low-level PM2.5 resulted in both pulmonary and extra-pulmonary changes characterized by alterations in systematic inflammation markers, cardiac repolarization, and decreased pulmonary function. A mean increase in PM2.5 concentration (37.8 μg/m3) significantly increased serum amyloid A (SAA), C-reactive protein (CRP), soluble intercellular adhesion molecule-1 (sICAM-1), and soluble vascular cell adhesion molecule-1 (sVCAM-1), 1 h after exposure by 8.7, 9.1, 10.7, and 6.6%, respectively, relative to the filtered air control. SAA remained significantly elevated (34.6%) 20 h after PM2.5 exposure which was accompanied by a 5.7% decrease in percent neutrophils. Decreased pulmonary function was observed 1 h after exposure through a 0.8 and 1.2% decrease in forced expiratory volume in 1 s (FEV1) and FEV1/ forced vital capacity (FEV1/FVC) respectively. Additionally, sex specific changes were observed in repolarization outcomes following PM2.5 exposure. In males, P-wave and QRS complex were increased by 15.4 and 5.4% 1 h after exposure. Conclusions This study is the first controlled human exposure study to demonstrate biological effects in response to exposure to concentrated ambient air PM2.5 particles at levels near the PM2.5 US NAAQS standard. Clinical trial registration information clinicaltrials.gov; Identifier: NCT03232086. The study was registered retrospectively on July 25, 2017, prior to final data collection on October 25, 2017 and data analysis.

scholarly journals Continuous mapping of fine particulate matter (PM<sub>2.5</sub>) air quality in East Asia at daily 6×6 km<sup>2</sup> resolution by application of a random forest algorithm to 2011–2019 GOCI geostationary satellite data

2021 ◽  
Author(s):  
Drew C. Pendergrass ◽  
Daniel J. Jacob ◽  
Shixian Zhai ◽  
Jhoon Kim ◽  
Ja-Ho Koo ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Random Forest ◽  
South Korea ◽  
East Asia ◽  
Fine Particulate Matter ◽  
Eastern China ◽  
Ambient Air ◽  
Population Exposure ◽  
Fine Particulate

Abstract. We use 2011–2019 aerosol optical depth (AOD) observations from the Geostationary Ocean Color Imager (GOCI) instrument over East Asia to infer 24-h daily surface fine particulate matter (PM2.5) concentrations at continuous 6x6 km2 resolution over eastern China, South Korea, and Japan. This is done with a random forest (RF) algorithm applied to the gap-filled GOCI AODs and other data and trained with PM2.5 observations from the three national networks. The predicted 24-h PM2.5 concentrations for sites entirely withheld from training in a ten-fold crossvalidation procedure correlate highly with network observations (R2 = 0.89) with single-value precision of 26–32 % depending on country. Prediction of annual mean values has R2 = 0.96 and single-value precision of 12 %. The RF algorithm is only moderately successful for diagnosing local exceedances of the National Ambient Air Quality Standard (NAAQS) because these exceedances are typically within the single-value precisions of the RF, and also because of RF smoothing of extreme PM2.5 concentrations. The area-weighted and population-weighted trends of RF PM2.5 concentrations for eastern China, South Korea, and Japan show steady 2015–2019 declines consistent with surface networks, but the surface networks in eastern China and South Korea underestimate population exposure. Further examination of RF PM2.5 fields for South Korea identifies hotspots where surface network sites were initially lacking and shows 2015–2019 PM2.5 decreases across the country except for flat concentrations in the Seoul metropolitan area. Inspection of monthly PM2.5 time series in Beijing, Seoul, and Tokyo shows that the RF algorithm successfully captures observed seasonal variations of PM2.5 even though AOD and PM2.5 often have opposite seasonalities. Application of the RF algorithm to urban pollution episodes in Seoul and Beijing demonstrates high skill in reproducing the observed day-to-day variations in air quality as well as spatial patterns on the 6 km scale. Comparison to a CMAQ simulation for the Korean peninsula demonstrates the value of the continuous RF PM2.5 fields for testing air quality models, including over North Korea where they offer a unique resource.

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