TY - JOUR
T1 - Prediction of tropospheric ozone concentrations by using the design system approach
AU - Abdul-Wahab, Sabah A.
AU - Abdo, Jamil
PY - 2007/1/1
Y1 - 2007/1/1
N2 - Data on the concentrations of non-methane hydrocarbons (NMHC), nitrogen oxide (NO), nitrogen dioxide (NO2), carbon monoxide (CO), and meteorological parameters (air temperature and solar radiation) were used to predict the concentration of tropospheric ozone using the Design-Ease software. These data were collected on hourly basis over a 12-month period. Sampling of the data was conducted automatically. The effect of the NMHC, NO, NO 2,CO, temperature and solar radiation variables in predicting ozone concentrations was examined under two scenarios: (i) when NO is included with the absence of NO2; and (ii) when NO2 is addressed with the absence of NO. The results of these two scenarios were validated against ozone actual data. The predicted concentration of ozone in the second scenario (i.e., when NO2 is addressed) was in better agreement with the real observations. In addition, the paper indicated that statistical models of hourly surface ozone concentrations require interactions and non-linear relationships between predictor variables in order to accurately capture the ozone behavior.
AB - Data on the concentrations of non-methane hydrocarbons (NMHC), nitrogen oxide (NO), nitrogen dioxide (NO2), carbon monoxide (CO), and meteorological parameters (air temperature and solar radiation) were used to predict the concentration of tropospheric ozone using the Design-Ease software. These data were collected on hourly basis over a 12-month period. Sampling of the data was conducted automatically. The effect of the NMHC, NO, NO 2,CO, temperature and solar radiation variables in predicting ozone concentrations was examined under two scenarios: (i) when NO is included with the absence of NO2; and (ii) when NO2 is addressed with the absence of NO. The results of these two scenarios were validated against ozone actual data. The predicted concentration of ozone in the second scenario (i.e., when NO2 is addressed) was in better agreement with the real observations. In addition, the paper indicated that statistical models of hourly surface ozone concentrations require interactions and non-linear relationships between predictor variables in order to accurately capture the ozone behavior.
KW - Air quality data
KW - Design system
KW - Factorial design
KW - Non-linear relationships
KW - Ozone
KW - Statistical models
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U2 - 10.1080/10934520601015388
DO - 10.1080/10934520601015388
M3 - Article
C2 - 17129943
AN - SCOPUS:33845298668
SN - 1093-4529
VL - 42
SP - 19
EP - 26
JO - Journal of Environmental Science and Health - Part A Toxic/Hazardous Substances and Environmental Engineering
JF - Journal of Environmental Science and Health - Part A Toxic/Hazardous Substances and Environmental Engineering
IS - 1
ER -