Prediction of tropospheric ozone concentrations by using the design system approach

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Abstract

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.

Original languageEnglish
Pages (from-to)19-26
Number of pages8
JournalJournal of Environmental Science and Health - Part A Toxic/Hazardous Substances and Environmental Engineering
Volume42
Issue number1
DOIs
Publication statusPublished - Jan 1 2007

Fingerprint

Ozone
nitrogen oxides
Nitrogen oxides
ozone
Nitric Oxide
prediction
nonmethane hydrocarbon
carbon monoxide
Carbon Monoxide
Hydrocarbons
solar radiation
Solar radiation
Carbon monoxide
Nitrogen Dioxide
nitrogen dioxide
Software design
air temperature
tropospheric ozone
software
Sampling

Keywords

  • Air quality data
  • Design system
  • Factorial design
  • Non-linear relationships
  • Ozone
  • Statistical models

ASJC Scopus subject areas

  • Environmental Engineering
  • Environmental Science(all)
  • Environmental Chemistry

Cite this

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title = "Prediction of tropospheric ozone concentrations by using the design system approach",
abstract = "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.",
keywords = "Air quality data, Design system, Factorial design, Non-linear relationships, Ozone, Statistical models",
author = "Abdul-Wahab, {Sabah A.} and Jamil Abdo",
year = "2007",
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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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