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Real Time Monitoring of Carbon Monoxide Using Value-at-Risk Measure and Control Charting

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  • Bersimis, Sotirios
  • Degiannakis, Stavros
  • Georgakellos, Dimitrios

Abstract

One of the most important environmental health issues is air pollution, causing the deterioration of the population’s quality of life, principally in cities where the urbanization level seems limitless. Among ambient pollutants, carbon monoxide (CO) is well known for its biological toxicity. Many studies report associations between exposure to CO and excess mortality. In this context, the present work provides an advanced modelling scheme for real time monitoring of pollution data and especially of carbon monoxide pollution in city level. The real time monitoring is based on an appropriately adjusted multivariate time series model that is used in finance and gives accurate one-step-ahead forecasts. On the output of the time series, we apply an empirical monitoring scheme that is used for the early detection of abnormal increases of CO levels. The proposed methodology is applied in the city of Athens and as the analysis revealed has a valuable performance.

Suggested Citation

  • Bersimis, Sotirios & Degiannakis, Stavros & Georgakellos, Dimitrios, 2015. "Real Time Monitoring of Carbon Monoxide Using Value-at-Risk Measure and Control Charting," MPRA Paper 65865, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:65865
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    More about this item

    Keywords

    Air Quality Surveillance; Atmospheric Pollution; Autoregressive Conditional Heteroskedasticity modelling; Control Charts; Diag-aVECH; Multivariate Statistical Process Monitoring; Multivariate Time Series; Value-at-Risk.;
    All these keywords.

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics
    • C40 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - General
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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