The purpose of the study is to generate traffic air information system） to determine a proper zone of AQMS （air analyzed were carbon monoxide （CO）, and nitrogen oxides （NOx） pollution map using mathematical mode...The purpose of the study is to generate traffic air information system） to determine a proper zone of AQMS （air analyzed were carbon monoxide （CO）, and nitrogen oxides （NOx） pollution map using mathematical model and GIS （geographic quality monitoring station） in municipality area. The pollutants which can be harmful to people living in the area. The three steps of mapping process were performed under the GIS environment using the existing vehicle emission rates and pollutant dispersion model. First, traffic volume, road network, and the emission rates of road segments varying with types of vehicle were collected from existing data. Second, the pollutant concentrations were calculated by use of CALINE4, a tool with Gaussian dispersion model. The model parameters include emission rate, wind directions and speeds, ambient temperature and observed pollutant concentration, and atmospheric stability during all seasons from the January 1, 2010 to May 31,2011 with regardless the rainy season. This resulted in concentrations at many receptor points along links of the road network. Third, distributions of pollution concentrations were generated by means of the spatial interpolation of those from receptors. The results of pollution raster-based maps are used for determining frequency of violence and combined pollution map. The resulting frequency of violence and intensity concentration will be further integrated to determine a potential area of AQMS. Finally, achieving pollution potential area of AQMS can be located as helpful basic data for efficient traffic and transportation planning.展开更多
This work aims to provide a methodology framework which allows to improve the performance and efficiency of an air quality monitoring network(AQMN).It requires to be constituted by a minimum and reliable number of mea...This work aims to provide a methodology framework which allows to improve the performance and efficiency of an air quality monitoring network(AQMN).It requires to be constituted by a minimum and reliable number of measurement sites.Nevertheless,the AQMN efficiency should be assessed over time,as a consequence of the possible emergence of new emission sources of air pollutants,which could lead to variations on their spatial distribution within the target area.PM_(10)particles data monitored by the Community of Madrid's(Spain)AQMN between 2008 and 2017 were used to develop a methodology to optimize the AQMN performance.The annual spatial distribution of average PM_(10)levels over the studied period monitored by all current stations vs those more representative was provided by a geographic information system(GIS),and the percentage of similarity between both postulates was quantified using simple linear regression(>95%).As one innovative tool of this study,the practical application of the proposed methodology was validated using PM_(10)particles data measured by AQMN during 2007 and 2018,reaching a similitude degree higher than 95%.The influence of temporal variation on the proposed methodological framework was around 20%.The proposed methodology sets criteria for identifying non-redundant stations within AQMN,it is also able to appropriately assess the representativeness of fixed monitoring sites within an AQMN and it complements the guidelines set by European legislation on air pollutants monitoring at fixed stations,which could help to tackle efforts to improve the air quality management.展开更多
文摘The purpose of the study is to generate traffic air information system） to determine a proper zone of AQMS （air analyzed were carbon monoxide （CO）, and nitrogen oxides （NOx） pollution map using mathematical model and GIS （geographic quality monitoring station） in municipality area. The pollutants which can be harmful to people living in the area. The three steps of mapping process were performed under the GIS environment using the existing vehicle emission rates and pollutant dispersion model. First, traffic volume, road network, and the emission rates of road segments varying with types of vehicle were collected from existing data. Second, the pollutant concentrations were calculated by use of CALINE4, a tool with Gaussian dispersion model. The model parameters include emission rate, wind directions and speeds, ambient temperature and observed pollutant concentration, and atmospheric stability during all seasons from the January 1, 2010 to May 31,2011 with regardless the rainy season. This resulted in concentrations at many receptor points along links of the road network. Third, distributions of pollution concentrations were generated by means of the spatial interpolation of those from receptors. The results of pollution raster-based maps are used for determining frequency of violence and combined pollution map. The resulting frequency of violence and intensity concentration will be further integrated to determine a potential area of AQMS. Finally, achieving pollution potential area of AQMS can be located as helpful basic data for efficient traffic and transportation planning.
文摘This work aims to provide a methodology framework which allows to improve the performance and efficiency of an air quality monitoring network(AQMN).It requires to be constituted by a minimum and reliable number of measurement sites.Nevertheless,the AQMN efficiency should be assessed over time,as a consequence of the possible emergence of new emission sources of air pollutants,which could lead to variations on their spatial distribution within the target area.PM_(10)particles data monitored by the Community of Madrid's(Spain)AQMN between 2008 and 2017 were used to develop a methodology to optimize the AQMN performance.The annual spatial distribution of average PM_(10)levels over the studied period monitored by all current stations vs those more representative was provided by a geographic information system(GIS),and the percentage of similarity between both postulates was quantified using simple linear regression(>95%).As one innovative tool of this study,the practical application of the proposed methodology was validated using PM_(10)particles data measured by AQMN during 2007 and 2018,reaching a similitude degree higher than 95%.The influence of temporal variation on the proposed methodological framework was around 20%.The proposed methodology sets criteria for identifying non-redundant stations within AQMN,it is also able to appropriately assess the representativeness of fixed monitoring sites within an AQMN and it complements the guidelines set by European legislation on air pollutants monitoring at fixed stations,which could help to tackle efforts to improve the air quality management.
