The Experts below are selected from a list of 19908 Experts worldwide ranked by ideXlab platform

Ayse Betul Oktay - One of the best experts on this subject based on the ideXlab platform.

  • forecasting air pollutant Indicator levels with geographic models 3days in advance using neural networks
    Expert Systems With Applications, 2010
    Co-Authors: Atakan Kurt, Ayse Betul Oktay
    Abstract:

    An early warning system for air quality control requires an accurate and dependable forecasting of pollutants in the air. In this study methods based on geographic forecasting models using neural networks (GFM_NN) are presented. The air pollutant data from 10 different air quality monitoring stations in Istanbul was used in forecasting sulfur dioxide (SO"2), carbon monoxide (CO) and particulate matter (PM"1"0) levels 3days in advance for the Besiktas district. Daily meteorological forecasts as well as the air pollutant Indicator values were used as input to feed-forward back-propagation neural networks. The experimental verification of the models was conducted in one-year period between August 2005 and August 2006. The observed and forecasted bands were used to compute the forecasting error. The simplest geographic model proposed uses the observed air Pollution Indicator values from a selected neighboring district. Where as the second model uses two neighboring districts instead of one. A third model considers the distance between the triangulating districts and the district whose air pollutant level is being forecasted. Each model is tested with at least two different sets of sites. The findings are quite satisfactory. When the right neighboring districts are chosen, the geographic models always yield lower error than non-geographic models. The distance-based geographic model produces considerably lower error than the non-geographic plain model. We argue that models proposed here can be used in urban air Pollution forecasting.

Bará Salvador - One of the best experts on this subject based on the ideXlab platform.

  • Monitoring transition: expected night sky brightness trends in different photometric bands
    'Elsevier BV', 2021
    Co-Authors: Bará Salvador, Rigueiro Iago, Lima, Raul Cerveira
    Abstract:

    Several light Pollution Indicators are commonly used to monitor the effects of the transition from outdoor lighting systems based on traditional gas-discharge lamps to solid-state light sources. In this work we analyze a subset of these Indicators, including the artificial zenithal night sky brightness in the visual photopic and scotopic bands, the brightness in the specific photometric band of the widely used Sky Quality Meter (SQM), and the top-of-atmosphere radiance detected by the VIIRS-DNB radiometer onboard the satellite Suomi-NPP. Using a single-scattering approximation in a layered atmosphere we quantitatively show that, depending on the transition scenarios, these Indicators may show different, even opposite behaviors. This is mainly due to the combined effects of the changes in the sources' spectra and angular radiation patterns, the wavelength- dependent atmospheric propagation processes and the differences in the detector spectral sensitivity bands. It is suggested that the possible presence of this differential behavior should be taken into account when evaluating light Pollution Indicator datasets for assessing the outcomes of public policy decisions regarding the upgrading of outdoor lighting systems.info:eu-repo/semantics/publishedVersio

  • Monitoring transition: expected night sky brightness trends in different photometric bands
    'Elsevier BV', 2019
    Co-Authors: Bará Salvador, Rigueiro Iago, Lima, Raul C.
    Abstract:

    Several light Pollution Indicators are commonly used to monitor the effects of the transition from outdoor lighting systems based on traditional gas-discharge lamps to solid-state light sources. In this work we analyze a subset of these Indicators, including the artificial zenithal night sky brightness in the visual photopic and scotopic bands, the brightness in the specific photometric band of the widely used Sky Quality Meter (SQM), and the top-of-atmosphere radiance detected by the VIIRS-DNB radiometer onboard the satellite Suomi-NPP. Using a single-scattering approximation in a layered atmosphere we quantitatively show that, depending on the transition scenarios, these Indicators may show different, even opposite behaviors. This is mainly due to the combined effects of the changes in the sources' spectra and angular radiation patterns, the wavelength-dependent atmospheric propagation processes and the differences in the detector spectral sensitivity bands. It is suggested that the possible presence of this differential behavior should be taken into account when evaluating light Pollution Indicator datasets for assessing the outcomes of public policy decisions regarding the upgrading of outdoor lighting systems.Comment: 28 pages, 7 fi

Atakan Kurt - One of the best experts on this subject based on the ideXlab platform.

  • forecasting air pollutant Indicator levels with geographic models 3days in advance using neural networks
    Expert Systems With Applications, 2010
    Co-Authors: Atakan Kurt, Ayse Betul Oktay
    Abstract:

    An early warning system for air quality control requires an accurate and dependable forecasting of pollutants in the air. In this study methods based on geographic forecasting models using neural networks (GFM_NN) are presented. The air pollutant data from 10 different air quality monitoring stations in Istanbul was used in forecasting sulfur dioxide (SO"2), carbon monoxide (CO) and particulate matter (PM"1"0) levels 3days in advance for the Besiktas district. Daily meteorological forecasts as well as the air pollutant Indicator values were used as input to feed-forward back-propagation neural networks. The experimental verification of the models was conducted in one-year period between August 2005 and August 2006. The observed and forecasted bands were used to compute the forecasting error. The simplest geographic model proposed uses the observed air Pollution Indicator values from a selected neighboring district. Where as the second model uses two neighboring districts instead of one. A third model considers the distance between the triangulating districts and the district whose air pollutant level is being forecasted. Each model is tested with at least two different sets of sites. The findings are quite satisfactory. When the right neighboring districts are chosen, the geographic models always yield lower error than non-geographic models. The distance-based geographic model produces considerably lower error than the non-geographic plain model. We argue that models proposed here can be used in urban air Pollution forecasting.

Lima, Raul Cerveira - One of the best experts on this subject based on the ideXlab platform.

  • Monitoring transition: expected night sky brightness trends in different photometric bands
    'Elsevier BV', 2021
    Co-Authors: Bará Salvador, Rigueiro Iago, Lima, Raul Cerveira
    Abstract:

    Several light Pollution Indicators are commonly used to monitor the effects of the transition from outdoor lighting systems based on traditional gas-discharge lamps to solid-state light sources. In this work we analyze a subset of these Indicators, including the artificial zenithal night sky brightness in the visual photopic and scotopic bands, the brightness in the specific photometric band of the widely used Sky Quality Meter (SQM), and the top-of-atmosphere radiance detected by the VIIRS-DNB radiometer onboard the satellite Suomi-NPP. Using a single-scattering approximation in a layered atmosphere we quantitatively show that, depending on the transition scenarios, these Indicators may show different, even opposite behaviors. This is mainly due to the combined effects of the changes in the sources' spectra and angular radiation patterns, the wavelength- dependent atmospheric propagation processes and the differences in the detector spectral sensitivity bands. It is suggested that the possible presence of this differential behavior should be taken into account when evaluating light Pollution Indicator datasets for assessing the outcomes of public policy decisions regarding the upgrading of outdoor lighting systems.info:eu-repo/semantics/publishedVersio

Lima, Raul C. - One of the best experts on this subject based on the ideXlab platform.

  • Monitoring transition: expected night sky brightness trends in different photometric bands
    'Elsevier BV', 2019
    Co-Authors: Bará Salvador, Rigueiro Iago, Lima, Raul C.
    Abstract:

    Several light Pollution Indicators are commonly used to monitor the effects of the transition from outdoor lighting systems based on traditional gas-discharge lamps to solid-state light sources. In this work we analyze a subset of these Indicators, including the artificial zenithal night sky brightness in the visual photopic and scotopic bands, the brightness in the specific photometric band of the widely used Sky Quality Meter (SQM), and the top-of-atmosphere radiance detected by the VIIRS-DNB radiometer onboard the satellite Suomi-NPP. Using a single-scattering approximation in a layered atmosphere we quantitatively show that, depending on the transition scenarios, these Indicators may show different, even opposite behaviors. This is mainly due to the combined effects of the changes in the sources' spectra and angular radiation patterns, the wavelength-dependent atmospheric propagation processes and the differences in the detector spectral sensitivity bands. It is suggested that the possible presence of this differential behavior should be taken into account when evaluating light Pollution Indicator datasets for assessing the outcomes of public policy decisions regarding the upgrading of outdoor lighting systems.Comment: 28 pages, 7 fi