Statistical analysis of aerosol species, trace gasses, and meteorology in Chicago

Binaku, Katrina; O’Brien, Timothy E.; Schmeling, Martina; Fosco, Tinamarie

doi:10.1007/s10661-013-3101-y

Cited by 9 publications

(14 citation statements)

References 21 publications

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“…Equilibrium is shifted from ammonium nitrate to gaseous nitric acid and ammonia in this case (Finlayson-Pitts and Pitts 2000). A similar result to PC1 was found when applying multivariate statistics to summer 2002-2004 data taken at the same location (Binaku et al 2013). Binaku et al (2013) suggested that organonitrate compounds play a role in the atmospheric signature of nitrate in Chicago.…”

Section: Principal Component Analysissupporting

confidence: 71%

“…A similar result to PC1 was found when applying multivariate statistics to summer 2002-2004 data taken at the same location (Binaku et al 2013). Binaku et al (2013) suggested that organonitrate compounds play a role in the atmospheric signature of nitrate in Chicago. Many urban studies have measured organonitrate compounds in the organic aerosol fraction.…”

Section: Principal Component Analysissupporting

confidence: 71%

“…Relationships between meteorology and air pollutants are important as both emission sources and weather regimes influence air quality episodes via transport and transformation of air pollutants across regions. Both principal component analysis (PCA) and canonical correlation analysis (CCA) have been applied to air pollution data collected from various locations (Binaku et al 2013;Binaku 2014;Braga et al 2005;Liu et al 2016;Statheropoulos et al 1998;Vasconcellos et al 2007;Yu and Chang 2006).…”

Section: Introductionmentioning

confidence: 99%

“…The summer 2010-2012 air pollution studies complimented a previous study completed at the same site during summers 2002-2004, of which aerosol, trace gas, and meteorological data were collected to assess air pollution and the local lake breeze as well as method development of aerosol analysis Schmeling 2006, 2007). Having completed multivariate analysis on the 2002-2004 summer data (Binaku et al 2013), PCA and CCA relationships between those data and the summer 2010-2012 data were assessed to identify similarities and differences in pollutant-pollutant or pollutant-meteorological variable relationships.…”

Section: Introductionmentioning

confidence: 99%

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Multivariate statistical analyses of air pollutants and meteorology in Chicago during summers 2010-2012

Binaku

Schmeling

2017

Air Qual Atmos Health

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Aerosol, trace gas, and meteorological data were collected in Chicago, Illinois during 2010-2012 summer air studies. Ozone, nitrogen oxides, acetate, formate, chloride, nitrate, sulfate, and oxalate concentrations as well as temperature, wind speed, wind direction, and humidity data were explored by both principal component analysis (PCA) and canonical correlation analysis (CCA). Multivariate statistical techniques were applied to uncover existing relationships between meteorology and air pollutant concentrations and also reduce data dimensions. In PCA, principal components (PC) revealed a relationship of ozone and nitrate concentrations with respect to temperature and humidity, coupled with transport of species from the south in relation to the sampling site (PC1). PC2 was a measure of secondary aerosols but also suggested acetate and formate presence was a result of primary emissions or transport. Both PC3 and PC4 contained residual information with the former representing days of lower pollution and the latter representing northerly wind transport of chloride, nitrate, and ozone to the sampling site. In CCA, three canonical functions were statistically significant. The first indicated high temperature and low wind speed had a strong linear relationship ozone, oxalate, and nitrogen oxides concentrations whereas the second function showed a strong influence of wind direction on acetate, formate, and chloride concentrations. Residuals of temperature, wind speed, trace gases, and oxalate also were in the second function. The only new information in the third function was humidity. Overall, PCA and CCA bring forth multi-variable relationships, not represented in descriptive statistics, useful in understanding pollution variability.

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Section: Principal Component Analysissupporting

confidence: 71%

Section: Principal Component Analysissupporting

confidence: 71%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Multivariate statistical analyses of air pollutants and meteorology in Chicago during summers 2010-2012

Binaku

Schmeling

2017

Air Qual Atmos Health

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“…Major point sources of particulate air pollution include 2 coal-fired power plants and metal processing, paint, and solvent factories (the last being in the southern and southeast parts of the city) (67). Mobile source emissions account for a majority of atmospheric nitrogen compounds, while refineries, coal burning, and steel manufacturing are responsible for sulfur compounds (67). The composition of airborne PM is primarily sulfate and organic carbons and secondary nitrates (68).…”

Section: Exposure Of Mice To Pmmentioning

confidence: 99%

β2-Adrenergic agonists augment air pollution–induced IL-6 release and thrombosis

Chiarella¹,

Soberanes²,

Urich³

et al. 2014

J. Clin. Invest.

112

101

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Acute exposure to particulate matter (PM) air pollution causes thrombotic cardiovascular events, leading to increased mortality rates; however, the link between PM and cardiovascular dysfunction is not completely understood. We have previously shown that the release of IL-6 from alveolar macrophages is required for a prothrombotic state and acceleration of thrombosis following exposure to PM. Here, we determined that PM exposure results in the systemic release of catecholamines, which engage the β 2 -adrenergic receptor (β 2 AR) on murine alveolar macrophages and augment the release of IL-6. In mice, β 2 AR signaling promoted the development of a prothrombotic state that was sufficient to accelerate arterial thrombosis. In primary human alveolar macrophages, administration of a β 2 AR agonist augmented IL-6 release, while the addition of a beta blocker inhibited PM-induced IL-6 release. Genetic loss or pharmacologic inhibition of the β 2 AR on murine alveolar macrophages attenuated PM-induced IL-6 release and prothrombotic state. Furthermore, exogenous β 2 AR agonist therapy further augmented these responses in alveolar macrophages through generation of mitochondrial ROS and subsequent increase of adenylyl cyclase activity. Together, these results link the activation of the sympathetic nervous system by β 2 AR signaling with metabolism, lung inflammation, and an enhanced susceptibility to thrombotic cardiovascular events.

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Spatio‐temporal variability of rainfall in a high tropical island: Patterns and large‐scale drivers in Réunion Island

Réchou¹,

Flores

Jumaux

et al. 2019

Quart J Royal Meteoro Soc

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Weather forecasting is challenging because of the complex interplay between local conditions and regional atmospheric forcings. In this article, we analyse the relationships between local daily rainfall and large‐scale synoptic patterns in the geographical context of Réunion Island, a high volcanic island in the southwestern Indian Ocean basin. Given the critical role of trade winds on weather conditions at island scale, we analyse those relationships across seasons defined with respect to yearly trade‐wind regimes. The analysis of the distribution of inversion events' elevation and frequency allows us to characterize the trade‐wind inversion layer (TWIL) and identify four seasons with homogeneous distributions. We characterize the spatio‐temporal variability of rainfall measured at island scale by a dense network of rain‐gauges over 37 years and relate it to large‐scale weather regimes identified using geopotential height meteorological data. After seasonal signal removal using Fourier transforms and dimension reduction via Principal Component Analysis, we perform Canonical Correlation Analysis to identify canonical variables relating rainfall and geopotential height patterns at the two different studied spatial scales. We then combine Ascending Hierarchical Classification and partitioning k‐means methods to identify homogeneous large‐scale synoptic conditions within each season. From this information, we build composite maps of geopotential height that characterize weather regimes and further analyse rainfall patterns at island scale in each regime. Elevation and orientation are used as descriptive variables at island scale as they strongly structure the patterns. Overall, four homogeneous seasons were identified based on trade‐wind regimes, within which six large‐scale weather regimes were identified for summer, the most variable season, and four for the others. Finally, rainfall patterns at island scale are described in relation to the highlighted synoptic regimes and local descriptive variables.

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Statistical analysis of aerosol species, trace gasses, and meteorology in Chicago

Cited by 9 publications

References 21 publications

Multivariate statistical analyses of air pollutants and meteorology in Chicago during summers 2010-2012

Multivariate statistical analyses of air pollutants and meteorology in Chicago during summers 2010-2012

β2-Adrenergic agonists augment air pollution–induced IL-6 release and thrombosis

Spatio‐temporal variability of rainfall in a high tropical island: Patterns and large‐scale drivers in Réunion Island

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