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  • Environmental Sciences.  (1)
  • Kalman filter  (1)
  • 1
    Online Resource
    Online Resource
    Urban Air Quality Monitoring, Modelling and Human Exposure Assessment (2021)
    Singapore :Springer Nature Singapore :
    Details
    Keywords: Environment. ; Pollution. ; Buildings Environmental engineering. ; Public health. ; Environmental Sciences. ; Pollution. ; Building Physics, HVAC. ; Public Health.
    Description / Table of Contents: Introduction -- Air Quality Monitoring Techniques -- Air Quality Modelling -- Air Quality Management and Control -- Indoor Air Quality -- Personal Exposure and Health Risk Assessment -- Smart Sensors for Air Quality Management.
    Abstract: This contributed volume is primarily intended for graduate and professional audiences. The book provides a basic understanding of urban air quality issues, root causes for local and urban air pollution, monitoring and modelling techniques, assessment, and control options to manage air quality at local and urban scale. The book also offers useful information on indoor air quality and smart sensors, which are gaining much importance in current times.
    Type of Medium: Online Resource
    Pages: XXX, 440 p. 173 illus., 127 illus. in color. , online resource.
    Edition: 1st ed. 2021.
    ISBN: 9789811555114
    Series Statement: Springer Transactions in Civil and Environmental Engineering,
    URL: https://doi.org/10.1007/978-981-15-5511-4
    DOI: 10.1007/978-981-15-5511-4
    DDC: 333.7
    Language: English
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    E-BOOKS (AWI ONLY)
  • 2
    Electronic Resource
    Electronic Resource
    Grey Box and Component Models to Forecast Ozone Episodes: A Comparison Study (2000)
    Springer
    Environmental monitoring and assessment 65 (2000), S. 313-321 
    Details
    ISSN: 1573-2959
    Keywords: ozone ; air pollution management ; time-series model ; cyclostationarity ; Kalman filter ; short-term forecasting
    Source: Springer Online Journal Archives 1860-2000
    Topics: Energy, Environment Protection, Nuclear Power Engineering
    Notes: Abstract For the purpose of short-term forecasting of high ozone concentration episodes stochastic models have been suggested and developed in the literature. The present paper compares the quality of forecasts produced by a grey box and a component time-series model. The summer ozone patterns for three European urban areas (two continental and one mediterranean) are processed. By means of forecast performance indices according to EC and WHO guidelines, the following features of the models could be found: The grey box model is highly adaptive and produces forecasts with low error variance that increases with the time horizon of forecast. The component model is more 'stiff' that results in a higher forecast-error variance and poorer adaption in detail. The forecast horizon, however, could be enlarged with this model. The accuracy of predicting threshold exceedance is similar for both models. This can be understood from the assumption of a cyclical time development of ozone that was made for both models.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1006496205139
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    Paper (German National Licenses)
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