A review of statistical methods for the meteorological adjustment of tropospheric ozone

Thompson, Mary Lou; Reynolds, Joel H.; Cox, Lawrence H.; Guttorp, Peter; Sampson, Paul D.

doi:10.1016/s1352-2310(00)00261-2

Cited by 213 publications

(128 citation statements)

References 39 publications

Supporting

Mentioning

124

Contrasting

Unclassified

Order By: Relevance

“…Thompson et al (2001) summarized the meteorological variables used in the literature for the statistical modelling of ozone. Surface temperature, wind speed and direction, and humidity were included in most models, while solar radiation and pressure were often available but not incorporated into the final models.…”

Section: Resultsmentioning

confidence: 99%

“…Some of those studies modelled separately the association between each ozone monitor and local meteorology (Cox and Chu, 1996;Joe et al, 1996), while the most complex analyses derived a univariate summary of the ozone monitoring network to capture regional associations between ozone and meteorology (Bloomfield et al, 1996;Davis et al, 1998). Thompson et al (2001) presented a critical review of those methods and compared the application of selected methods to ozone time series from the Chicago area.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Changes of daily surface ozone maxima in Switzerland in all seasons from 1992 to 2002 and discussion of summer 2003

et al. 2005

View full text Add to dashboard Cite

Abstract. An Analysis of Covariance (ANCOVA) was used to derive the influence of the meteorological variability on the daily maximum ozone concentrations at 12 low-elevation sites north of the Alps in Switzerland during the four seasons in the 1992-2002 period. The afternoon temperature and the morning global radiation were the variables that accounted for most of the meteorological variability in summer and spring, while other variables that can be related to vertical mixing and dilution of primary pollutants (afternoon global radiation, wind speed, stability or day of the week) were more significant in winter. In addition, the number of days after a frontal passage was important to account for ozone build-up in summer and ozone destruction in winter. The statistical model proved to be a robust tool for reducing the impact of the meteorological variability on the ozone concentrations. The explained variance of the model, averaged over all stations, ranged from 60.2% in winter to 71.9% in autumn. The year-to-year variability of the seasonal medians of daily ozone maxima was reduced by 85% in winter, 60% in summer, and 50% in autumn and spring after the meteorological adjustment. For most stations, no significantly negative trends (at the 95% confidence level) of the summer medians of daily O 3 or O x (O 3 +NO 2 ) maxima were found despite the significant reduction in the precursor emissions in Central Europe. However, significant downward trends in the summer 90th percentiles of daily O x maxima were observed at 6 sites in the region around Zürich (on average −0.73 ppb yr −1 for those sites). The lower effect of the titration by NO as a consequence of the reduced emissions could partially explain the significantly positive O 3 trends in the cold seasons (on average 0.69 ppb yr −1 in winter and 0.58 ppb yr −1 in autumn). The increase of O x found for most stations in autumn (on average 0.23 ppb yr −1 ) and winter (on average 0.39 ppb yr −1 ) could be due to increasing European background ozone levCorrespondence to: A. S. H. Prévôt (andre.prevot@psi.ch) els, in agreement with other studies. The statistical model was also able to explain the very high ozone concentrations in summer 2003, the warmest summer in Switzerland for at least ∼150 years. On average, the measured daily ozone maximum was 15 ppb (nearly 29%) higher than in the reference period summer 1992-2002, corresponding to an excess of 5 standard deviations of the summer means of daily ozone maxima in that period.

show abstract

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Changes of daily surface ozone maxima in Switzerland in all seasons from 1992 to 2002 and discussion of summer 2003

et al. 2005

View full text Add to dashboard Cite

show abstract

“…These methods generally make use of statistical techniques such as regression or other data-fitting methods using numerical techniques to establish the respective relationships between the various physicochemical parameters and variable of interest based on routinely-measured historical data. The main objectives of these methods include investigating and assessing trends in air quality, making environmental forecasts and increasing scientific understanding of the mechanisms that govern air quality (Thompson et al, 2001). Among the techniques being examined to relate air quality in a given area to measured physical and chemical parameters, the three that have been used most often are i) multivariate regression (Hubbard & Cobourne, 1998, Comrie & Diem, 1999, Davis & Speakman, 1999Draxler, 2000, Gardner & Dorling, 2000, ii) artificial neural networks (ANN) (Perez & Reyes, 2006;Brunelli et al, 2006;Thomas & Jacko, 2007;Grivas & Chaloulakou, 2005;Gardner & Dorling, 1999), and iii) time series and spectral analysis (Raga & Moyne, 1996, Chen et al, 1998Milanchus et al, 1998, Salcedo et al, 1999, Sebald et al, 2000.…”

Section: Introductionmentioning

confidence: 99%

Artificial Neural Network Models for Prediction of Ozone Concentrations in Guadalajara, Mexico

García¹,

Rodríguez²,

Tenorio³

2011

Air Quality-Models and Applications

View full text Add to dashboard Cite

“…In the present paper, the data set collection consists of 10-year long daily observations of • maximum ozone concentration levels (consisting of pairs of values related to "present" and "previous" day conditions in ìg m -3 ), • maximum ozone concentration levels until 13:00 p.m. (ìg m -3 ) coming from the AQ monitoring network, • maximum and mean daily temperature (°C), • total solar radiation (W m -2 ), and • mean wind speed (m s -1 ), coming from the meteorological observation station of the National Observatory of Athens for the same time period. The choice of meteorological variables was based upon selecting those that were generally available and widely accepted as being associated to ozone formation (Gardner and Dorling, 2000;van Aalst and Leeuw, 1997;Thompson et al, 2001), since this would facilitate the results of this work being applied in a forecasting mode: Temperature plays a crucial role, as with increasing temperature, the ozone concentration is expected to rise. Another favourable condition is the wind speed, as mixing drops with lower wind speeds, while photochemical reactions, which represent one source of ozone formation, depend on the amount of solar radiation (Rappengluck et al, 1993).…”

Section: Methodsmentioning

confidence: 99%

Regression Analysis and urban air quality forecasting: an application for the city of Athens

2013

Global NEST Journal

View full text Add to dashboard Cite

Air pollution forecasts in major urban areas are becoming a problem concerning the day to day environmental management for city authorities. This paper describes the development of an application to forecast the peak ozone levels with the aid of meteorological and air quality variables, in the Greater Athens Area. For this purpose, a number of regression models were considered, while the selection of the final model was based on extensive analysis and on literature. The model adapted includes variables that are available on a daily basis, so as daily operational maximum ozone concentration level forecast can be achieved.

show abstract

A review of statistical methods for the meteorological adjustment of tropospheric ozone

Cited by 213 publications

References 39 publications

Changes of daily surface ozone maxima in Switzerland in all seasons from 1992 to 2002 and discussion of summer 2003

Changes of daily surface ozone maxima in Switzerland in all seasons from 1992 to 2002 and discussion of summer 2003

Artificial Neural Network Models for Prediction of Ozone Concentrations in Guadalajara, Mexico

Regression Analysis and urban air quality forecasting: an application for the city of Athens

Contact Info

Product

Resources

About