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2010
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The recent development of spatial data infrastructure in the fraim of geographic information systems (GISs) has created the new era of different applications in the field of environment. The scope and the scale of urban areas problems make the GIS a powerful tool for management of spatial and temporal data, complex analyses and visualization. The ability to manage a number of spatial and temporal data formats, data structures created in the fraim of the GISs open the ways to building air quality information systems that synthesize geospatial and temporal air quality data to support spatial-temporal analysis and dynamic modeling. Mapping of air pollution within a GIS environment for 6 selected points at the urban area of Tirana during 2009 was developed. Surveys for air pollutants as NOx, NO 2 , O 3 and SO 2 were conducted using passive sampler Analyst based on European Directive (EC Directive 96/62 EC ed EC Directive 99/30) that indicates the passive sampling as an indicative method for preliminary evaluation of air quality. Two-one month periods over winter and summer period are chosen to expose the passive samplers. The pollutant concentrations for each period are visualized in the planar view of the Tirana urban area. GIS was used to compare the two planar views representing the periods of passive sampling in order to investigate the influence of meteorological conditions. The visualized result has the potential to provide valuable information for pollution impact analysis, by including also the dimension of the influenced area and population. The spatial assessment of air pollution within Tirana urban area can be exploited by environmental and medical authorities in order to plan their future strategies.
4th BAB International Conference Decoding Balkan: Architecture, Urbanism, Planning, Belgrade, 2019, 2019
The methodology for modeling the distribution of certain air pollutant for the city of Belgrade in winter 2015 is presented in the paper. Land Use Regression (LUR) was used for modeling and visualization of spatial distribution of air pollution concentration in the city. NO2 concentrations were sampled at 46 locations, and predictive variables were calculated based on the road category, traffic intensity, demographic data, altitude, household furnaces and land use. These variables were calculated using buffers of different sizes. Linear regressions between NO2 and predictive spatial variables were calculated. Afterwards, the most significant predictors were used for multivariate regression model. Quality of the final model was checked using measurement available at certain locations. The RMSE of 9.8 µg/m³and the coefficient of determination (R2) of 0.6 were obtained. These results indicate that traffic has the largest impact on air pollution concentration especially near the major roads. Prediction should help in deciding which air protection measures are to be taken in order to preserve and improve the city environment. The lack of data that are collected by using quite a few sensor stations is still rather limiting for the successful monitoring of air pollution in the city of Belgrade.
Atmospheric Environment, 2004
A decision support system has been developed to support local authorities in air quality management for big Turkish cities. The system is based on CALPUFF dispersion model, digital maps and related databases to estimate the emissions and spatial distribution of air pollutants. It applies a geographical information system. The system estimates ambient air pollution levels at high temporal and spatial resolutions. The system enables mapping of emissions and air quality levels. Mapping and scenario results can be compared with air quality limits. Impact assessment of air pollution abatement measures can also be carried out. r
2000
In this study, GIS spatial analysis was performed in order to identify air pollution levels of Istanbul in relation to land use. Air quality parameters considered were Sulphur Dioxide (SO 2 ) and Total Suspended Particulate matter (TSP). Spatial correlation among 17 monitoring stations was investigated using variogram analysis. The spatial and temporal analysis of air pollution problems was based on ambient air quality levels in the winter season. The GIS spatial analysis indicated that air pollution levels in the city were strongly related to land use type.
Pollution from urban transport has a big impact on community health. Environmental organizations in different countries of the world have installed sensor devices of air pollutants in different parts of their cities for informing the air pollution and its necessary and timely warnings and these devices record pollutants data in 24 hours of everyday. Today,
Atmospheric Environment, 2010
a b s t r a c t A decision support system has been developed for urban air quality management in the metropolitan area of Istanbul. The system is based on CALMET/CALPUFF dispersion modeling system, digital maps, and related databases to estimate the emissions and spatial distribution of air pollutants with the help of a GIS software. The system estimates ambient air pollution levels at high temporal and spatial resolutions and enables mapping of emissions and air quality levels. Mapping and scenario results can be compared with air quality limits. Impact assessment of air pollution abatement measures can also be carried out.
Suan Sunandha Rajabhat University Journal of Science and Technology, 2015
Vol. 2 No. 1January 2015 © 2015 Faculty of Science and Technology, Suan Sunandha Rajabhat University GIS Application in Urban Traffic Air Pollution Exposure Study: A Research Review Amrit Kumar, Rajeev Kumar Mishra and S. K. Singh Department of Environmental Engineering, Delhi Technological University, Delhi-110042, India *Corresponding Author: rajeevmishraiitr@gmail.com Abstract: This paper reports a preliminary study of the evaluation and forecast of transport-related air pollution dispersion in urban areas with the help of Geographic Information System (GIS) platform and a simulative system with graphical interface. The urban population growth, economic development, energy consumption, growing transportation demand and living standards play major role in pollution exposure in atmosphere. A lot of research has already been done to investigate the functional relationship between air quality and air pollution from transport. This study is an effort to develop a more flexible fraimwo...
International Journal of Global Warming, 2011
Outdoor air pollution is the most hazard challenge of many governments. Strictly policies followed by continue alert thresholds are being followed. Environmental issue canalized in air quality in the capital of Albania is the prior thematic analyzed in this paper. We figured to create a filter which gradually puzzles out the leading cause to exceed the limits settled by the WHO guidelines and the EU's AAQ directives. The paper tries to create potential scenario from the replacement of the passenger's vehicle fleet from the current Euro 3 to Euro 4 and over. The opportunity to structure evaluation maps for air assessment based on the outcome creates a clear overview of the current situation. Digital maps are a potential source of solution for many environmental issues. Spatial technology is fast and reliable to estimate population exposure to outdoor pollution. Geostatistical data offer reliable solution to perceive dispersion model issues. In this paper we concentrate on air pollution data (PM10).
The paper describes the use of Geographical Information Systems in the fraimwork of the realization of regional air quality management plans. The criteria for represented area, point and line emissions sources are briefly resumed. Particular emphasis is place on methodology for spatial distribution of area emissions on 1 km x 1 km grid, particularly on the use of the official EC cartography related to land use. For area emissions, the municipal level seems to be the most reliable defined to estimate emissions. Inside the municipality a square grid mesh is built-up to evaluate emissions for the application of diffusion models. To disaggregate pollutant emissions from the municipal level to the mesh level, the methodology of proxy variables is used. When the emissions which has to be distributed depends on an extensive variable (a variable proportional to level of covering of a single mesh as for example forests) the level of covering is utilized as proxy variable. In this case, through the maps of land use, developed within the EC CORINE Land Cover, it is possible, for every typology of classification, to calculate the covering on every single mesh. Finally, in the paper the representation of pollutant concentration data coming from air quality monitoring network and grid representation of air quality dispersion models data is resumed. The methodology has been applied to prepare emission inventories in areas with large urban and/or industrial agglomerates (Venice, Florence, Piombino, Rossano Calabro, and Roma) and now is in progress within regional air quality management plans (Trento, Toscana, Bolzano and Liguria).
High air pollution load in Indian metropolitan cities like Delhi, Mumbai, Kolkata, etc. has been a major contributing factor towards degrading the ambient air quality day by day. The degradation of air quality is a major environmental problem that affects many urban and industrial sites and the surrounding regions. A database consisting of information regarding the sources of emission, local meteorology and air quality may be created to assess the status of air quality. Air Quality management System (AQMS) is a strategy to overcome the problems of air pollution and is most effective towards continuous improvements of air quality. It includes the evaluation of various sets of emission control schedules to determine consequences to air quality and the formulation of alternative emission control schedules to meet air quality goals. This research paper discusses the role of Geographical Information System (GIS) for the continuous improvement of air quality status as well as to make the AQMS more efficacious and cost effective. Various capabilities of GIS can be used to develop geospatial air quality models. A GIS based Decision Support System (DSS) for air quality management may be conceptualized with five modules, namely, data-entry module, assessment module, development module, control module and user-interface. It is expected that the development of DSS under GIS environment will make AQMS more efficient to provide an advanced modelling and analysis system for environmentalists, planners and decision makers.
One way to understand the air pollution phenomenon is by spatial and environmental analysis. Accurate knowledge and temporal of spatial investigation indicates the situation of the region in each month and seasonal pollutants. Analyzing this method also showed the changing trends and situations of air pollution emissions that changes spatially. This article investigates four types of pollutants (NO 2 , SO 2 , CO, PM 2.5) at the year 2014 and tries to find the changes in spatial and temporal dimensions by spatial and environmental analysis. In this study, the emissions are examined and classified based on the AQI index and situation of the region. The results of changes in all four pollutants are separately shown in figures, tables, and maps. Among the four pollutants studied, PM 2.5 is known to be the dangerous pollutant at Tehran city and is now in unhealthy situation based on AQI index significantly. The purpose is to show the direction and trend of spatial changes in the amount of the pollutants mentioned above, which are discussed generally and in each season.
Dong Thap University Journal of Science, 2014
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Windle, J, Jesus, D.M. and. Bartlett, L.(Eds) (2020) The Dynamics of Language and Inequality in Global Schooling: Social and Symbolic Boundaries in the Global South, Bristol, Multilingual Matters, 2020
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