Characterization and Identification of Trends in Average Ambient Ozone and Fine Particulate Matter Levels through Trajectory Cluster Analysis in Eastern Canada

2007 ◽  
Vol 57 (8) ◽  
pp. 907-918 ◽  
Author(s):  
David Johnson ◽  
Domenico Mignacca ◽  
Dennis Herod ◽  
Daniel Jutzi ◽  
Heather Miller
2019 ◽  
Vol 171 ◽  
pp. 218-227 ◽  
Author(s):  
John A. Kaufman ◽  
J. Michael Wright ◽  
Glenn Rice ◽  
Natalia Connolly ◽  
Katherine Bowers ◽  
...  

Author(s):  
Yusuf Aina ◽  
Elhadi Adam ◽  
Fethi Ahmed

The study of the concentrations and effects of fine particulate matter in urban areas have been of great interest to researchers in recent times. This is due to the acknowledgment of the far-reaching impacts of fine particulate matter on public health. Remote sensing data have been used to monitor the trend of concentrations of particulate matter by deriving aerosol optical depth (AOD) from satellite images. The Center for International Earth Science Information Network (CIESIN) has released the second version of its global PM2.5 data with improvement in spatial resolution. This paper revisits the study of spatial and temporal variations in particulate matter in Saudi Arabia by exploring the cluster analysis of the new data. Cluster analysis of the PM2.5 values of Saudi cities is performed by using Anselin local Moran’s I statistic. Also, the analysis is carried out at the regional level by using self-organizing map (SOM). The results show an increasing trend in the concentrations of particulate matter in Saudi Arabia, especially in some selected urban areas. The eastern and south-western parts of the Kingdom have significantly clustering high values. Some of the PM2.5 values have passed the threshold indicated by the World Health Organization (WHO) standard and targets posing health risks to Saudi urban population.


2018 ◽  
Vol 236 ◽  
pp. 591-597 ◽  
Author(s):  
Hsiao-Chi Chuang ◽  
Ruei-Hao Shie ◽  
Chia-Pin Chio ◽  
Tzu-Hsuen Yuan ◽  
Jui-Huan Lee ◽  
...  

2021 ◽  
Vol 131 (1) ◽  
pp. 67-70
Author(s):  
Mieczysław Szyszkowicz ◽  
Nicholas De Angelis

Abstract Introduction. This study investigates associations between air pollution and emergency department (ED) visits for urticaria in Toronto, Canada. Aim. To verify the hypothesis that urticaria are related to air pollution. Material and methods. The National Ambulatory Care Reporting System database is used to draw the daily ED visits. The L50 section of the International Classification of Disease 10th Revision is applied to extract ED visits whose primary causes was urticaria-related skin condition. Statistical models (condition Poisson regression) using daily counts of ED visits are constructed for urticaria (health response) with ambient air pollution concentrations and weather factors as independent variable. Two air quality health indexes and six ambient air pollutants: fine particulate matter PM2.5, O3, CO, NO2, SO2, and maximum 8-hour average ozone are considered as an exposure. Results. A total of 176 statistically significant (P-Value <0.05) positive correlations were identified over the 15 day lag period (0-14 days). For daily average of ambient ozone, 74 positive correlations were observed with the following relative risks (RR) for a one interquartile range (IQR=12.8 ppb) increase: RR=1.361 (95% confidence interval: 1.302, 1.404), 1.359 (1.299, 1.401), 1.351 (1.281, 1.404) in the warm season (April-September), lag 0, and RR=1.019 (1.013, 1.025), 1.023 (1.016, 1.030), 1.014 (1.007, 1.021), lag 1, in the cold period (October-March), for all, females, and males, respectively. 10, 45 and 45 positive correlations were also obtained for sulfur dioxide, fine particulate matter, and daily maximum 8-hour average ozone concentrations, respectively. Conclusions. The results indicate that urban ambient air pollution could influence the numbers of ED visits for urticaria. Ambient ozone was determined as the main environmental factor contributing to these associations.


2020 ◽  
Author(s):  
Yazhen Gong ◽  
Shanjun Li ◽  
Nicholas Sanders ◽  
Guang Shi

2021 ◽  
pp. 106386
Author(s):  
Heyu Yin ◽  
Sina Parsnejad ◽  
Ehsan Ashoori ◽  
Hao Wan ◽  
Wen Li ◽  
...  

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