The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLIII-B4-2021
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B4-2021, 87–94, 2021
https://doi.org/10.5194/isprs-archives-XLIII-B4-2021-87-2021
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B4-2021, 87–94, 2021
https://doi.org/10.5194/isprs-archives-XLIII-B4-2021-87-2021

  30 Jun 2021

30 Jun 2021

COLLABORATIVE AIR QUALITY MAPPING OF DIFFERENT METROPOLITAN CITIES OF INDIA

R. Dubey, S. Bharadwaj, M. I. Zafar, and S. Biswas R. Dubey et al.
  • Dept. of Chemical Engineering and Engineering Sciences, Rajiv Gandhi Institute of Petroleum Technology Jais, Amethi, Uttar Pradesh, India

Keywords: Air pollution, air quality mapping, Dispersion, GIS Mapping, Interpolation, Modeling, Road Traffic

Abstract. Environmental pollution has become extremely serious as a result of today's technological advancements all over the world. One of the most important environmental and public health risks is air pollution. The exponential growth of population, vehicular density on highways, urbanization, and other factors are rising air pollution in cities, necessitating techniques for monitoring and forecasting air quality or determining its health consequences. Various experiments are being conducted on city air quality and its distribution through the built climate. The amount of emissions in the air varies according to the time of day as depicted it is merely high in morning time between 9 to 10 am and between 5 to 6 pm in all cities. These collected data are also characterized as peak hour, average hour, and off-peak hour. It also varies geographically and during special occasions. Since computing and showcasing of air pollution levels require terrain data, air quality data from the open sources i.e. CPCB (central pollution control board, India), and air pollution prediction models. Acculumating the data of the air pollution parameter from the open sources of cities based on typically very crowded, averagely crowded, and thinly crowded areas across the city and then mapping it on ArcGIS. The data monitoring has been done for the whole year merely main emphasizes has been done on the three seasons autumn, winter, and summer (January, May, and August). Also, in winter the value of having pollutants is high due to winter inversion and in the morning also the value is higher, and in monsoon, due to precipitation, it decreases. The dispersion model help in considering the wind speed and direction, the computed data from each source location reaching out to the monitoring sensing station from the comparatively adding to the value of pollutant. With the help of questionnaires, computed out to the result that people residing or having the workplace near to the busy crossing are more promising to have the health-related issue like chocking, respiratory diseases. Men are merely more affected by this between the age of 37 to 63 years.