scholarly journals PROSPECTIVE HEALTH RISK OF EXPOSURE TO FINE PARTICULATE MATTER AND ITS ELEMENTAL COMPOSITION IN SHOE INDUSTRIES IN AGRA

2015 ◽  
Vol 9 (2) ◽  
pp. 11-22
Author(s):  
Mansi Gupta ◽  
Renuka Saini ◽  
Ajay Taneja
Keyword(s):  
Particulate Matter ◽  
Health Risk ◽  
Elemental Composition ◽  
Fine Particulate Matter ◽  
Fine Particulate ◽  
Risk Of Exposure

Elemental composition of fine particulate matter (PM2.5) in Skopje, FYR of Macedonia

2011 ◽  
Vol 40 (4) ◽  
pp. 280-288 ◽  
Author(s):  
Borka Kovacevik ◽  
Annemarie Wagner ◽  
Johan Boman ◽  
Jens Laursen ◽  
Jan B. C. Pettersson
Keyword(s):  
Particulate Matter ◽  
Elemental Composition ◽  
Fine Particulate Matter ◽  
Fine Particulate

scholarly journals Evaluation of Using Satellite-Derived Aerosol Optical Depth in Land Use Regression Models for Fine Particulate Matter and Its Elemental Composition

Atmosphere ◽  
2021 ◽  
Vol 12 (8) ◽  
pp. 1018
Author(s):  
Chun-Sheng Huang ◽  
Ho-Tang Liao ◽  
Tang-Huang Lin ◽  
Jung-Chi Chang ◽  
Chien-Lin Lee ◽  
...  
Keyword(s):  
Land Use ◽  
Particulate Matter ◽  
Elemental Composition ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Prediction Models ◽  
Fine Particulate Matter ◽  
Sensitivity Analyses ◽  
Land Use Regression ◽  
Fine Particulate

This study introduced satellite-derived aerosol optical depth (AOD) in land use regression (LUR) modeling to predict ambient concentrations of fine particulate matter (PM2.5) and its elemental composition. Twenty-four daily samples were collected from 17 air quality monitoring sites (N = 408) in Taiwan in 2014. A total of 12 annual LUR models were developed for PM2.5 and 11 elements, including aluminum, calcium, chromium, iron, potassium, manganese, sulfur, silicon, titanium, vanadium, and zinc. After applied AOD and a derived-predictor, AOD percentage, in modeling, the number of models with leave-one-out cross-validation R2 > 0.40 significantly increased from 5 to 9, indicating the substantial benefits for the construction of spatial prediction models. Sensitivity analyses of using data stratified by PM2.5 concentrations revealed that the model performances were further improved in the high pollution season.

Elemental composition of fine particulate matter and risk for hypertension

2016 ◽  
Vol 2016 (1) ◽  
Author(s):  
Fuks Kateryna* ◽  
Frauke Hennig ◽  
Dorothee Sugiri ◽  
Ulrich Quass ◽  
Susanne Moebus ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Elemental Composition ◽  
Fine Particulate Matter ◽  
Fine Particulate

Trends in the Elemental Composition of Fine Particulate Matter in Santiago, Chile, from 1998 to 2003

2007 ◽  
Vol 57 (7) ◽  
pp. 845-855 ◽  
Author(s):  
Sonja N. Sax ◽  
Petros Koutrakis ◽  
Pablo A. Ruiz Rudolph ◽  
Francisco Cereceda-Balic ◽  
Ernesto Gramsch ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Elemental Composition ◽  
Fine Particulate Matter ◽  
Fine Particulate
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