Sensitivity analysis of ground-level ozone concentration to emission changes in two urban regions of southeast Texas

2005 ◽  
Vol 75 (4) ◽  
pp. 315-323 ◽  
Author(s):  
Che-Jen Lin ◽  
Thomas C. Ho ◽  
Hsing-wei Chu ◽  
Heng Yang ◽  
Santosh Chandru ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Ozone Concentration ◽  
Ground Level ◽  
Ground Level Ozone ◽  
Urban Regions ◽  
Southeast Texas ◽  
Emission Changes

scholarly journals The ground-level ozone concentration is inversely correlated with the number of COVID-19 cases in Warsaw, Poland

2021 ◽  
Author(s):  
Oskar Wiśniewski ◽  
Wiesław Kozak ◽  
Maciej Wiśniewski
Keyword(s):  
Wind Speed ◽  
Ozone Concentration ◽  
Inverse Correlation ◽  
Ground Level ◽  
Viral Agent ◽  
The Novel ◽  
Weather Factors ◽  
Ground Level Ozone ◽  
The Many ◽  
The Impact

AbstractCOVID-19, which is a consequence of infection with the novel viral agent SARS-CoV-2, first identified in China (Hubei Province), has been declared a pandemic by the WHO. As of September 10, 2020, over 70,000 cases and over 2000 deaths have been recorded in Poland. Of the many factors contributing to the level of transmission of the virus, the weather appears to be significant. In this work, we analyze the impact of weather factors such as temperature, relative humidity, wind speed, and ground-level ozone concentration on the number of COVID-19 cases in Warsaw, Poland. The obtained results show an inverse correlation between ground-level ozone concentration and the daily number of COVID-19 cases.

scholarly journals Spatial–Temporal Distribution Variation of Ground-Level Ozone in China’s Pearl River Delta Metropolitan Region

2021 ◽  
Vol 18 (3) ◽  
pp. 872
Author(s):  
An Zhang ◽  
Jinhuang Lin ◽  
Wenhui Chen ◽  
Mingshui Lin ◽  
Chengcheng Lei
Keyword(s):  
Ozone Concentration ◽  
Pearl River Delta ◽  
Temporal Distribution ◽  
Ground Level ◽  
Metropolitan Region ◽  
Pearl River ◽  
Ozone Pollution ◽  
Ground Level Ozone ◽  
Ozone Concentrations ◽  
The North

Long-term exposure to ozone pollution will cause severe threats to residents’ physical and mental health. Ground-level ozone is the most severe air pollutant in China’s Pearl River Delta Metropolitan Region (PRD). It is of great significance to accurately reveal the spatial–temporal distribution characteristics of ozone pollution exposure patterns. We used the daily maximum 8-h ozone concentration data from PRD’s 55 air quality monitoring stations in 2015 as input data. We used six models of STK and ordinary kriging (OK) for the simulation of ozone concentration. Then we chose a better ozone pollution prediction model to reveal the ozone exposure characteristics of the PRD in 2015. The results show that the Bilonick model (BM) model had the highest simulation precision for ozone in the six models for spatial–temporal kriging (STK) interpolation, and the STK model’s simulation prediction results are significantly better than the OK model. The annual average ozone concentrations in the PRD during 2015 showed a high spatial variation in the north and east and low in the south and west. Ozone concentrations were relatively high in summer and autumn and low in winter and spring. The center of gravity of ozone concentrations tended to migrate to the north and west before moving to the south and then finally migrating to the east. The ozone’s spatial autocorrelation was significant and showed a significant positive correlation, mainly showing high-high clustering and low-low clustering. The type of clustering undergoes temporal migration and conversion over the four seasons, with spatial autocorrelation during winter the most significant.

scholarly journals A data-driven approach to forecasting ground-level ozone concentration

2021 ◽  
Author(s):  
Dario Marvin ◽  
Lorenzo Nespoli ◽  
Davide Strepparava ◽  
Vasco Medici
Keyword(s):  
Ozone Concentration ◽  
Ground Level ◽  
Data Driven ◽  
Ground Level Ozone ◽  
Data Driven Approach

Stochastic model to forecast ground-level ozone concentration at urban and rural areas

Chemosphere ◽  
2005 ◽  
Vol 61 (10) ◽  
pp. 1379-1389 ◽  
Author(s):  
C. Dueñas ◽  
M.C. Fernández ◽  
S. Cañete ◽  
J. Carretero ◽  
E. Liger
Keyword(s):  
Stochastic Model ◽  
Ozone Concentration ◽  
Rural Areas ◽  
Ground Level ◽  
Ground Level Ozone ◽  
Urban And Rural Areas

scholarly journals The ground level ozone concentration is inversely correlated with the number of COVID-19 cases in Warsaw, Poland

2020 ◽  
Author(s):  
Oskar Wisniewski ◽  
Wieslaw Kozak ◽  
Maciej Wisniewski
Keyword(s):  
Wind Speed ◽  
Ozone Concentration ◽  
Inverse Correlation ◽  
Ground Level ◽  
Viral Agent ◽  
The Novel ◽  
Weather Factors ◽  
Ground Level Ozone ◽  
The Many ◽  
The Impact

COVID-19, which is a consequence of infection with the novel viral agent SARS-CoV-2, first identified in China (Hubei Province), has been declared a pandemic by the WHO. As of September 10, 2020, over 70,000 cases and over 2,000 deaths have been recorded in Poland. Of the many factors contributing to the level of transmission of the virus, the weather appears to be significant. In this work we analyse the impact of weather factors such as temperature, relative humidity, wind speed and ground level ozone concentration on the number of COVID-19 cases in Warsaw, Poland. The obtained results show an inverse correlation between ground level ozone concentration and the daily number of COVID-19 cases.

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