Air quality mapping using GIS and economic evaluation of health impact for Mumbai city, India
Creators: name: Kumar, Awkash
name: Gupta, Indrani
name: Brandt, Jørgen
name: Kumar, Rakesh
name: Kumar Dikshit, Anil
name: S Patil, Rashmi
Publisher: name: Taylor & Francis
Year: 2016
Subjects: subject: Space Science
subject: Medicine
subject: Biotechnology
subject: Environmental Sciences not elsewhere classified
subject: Chemical Sciences not elsewhere classified
subject: Ecology
subject: FOS: Biological sciences
subject: Sociology
subject: FOS: Sociology
subject: Marine Biology
subject: Science Policy

description: Mumbai a highly populated city in India has been selected for air quality mapping and assessment of health impact using monitored air quality data. Air quality monitoring networks in Mumbai are operated by National Environment Engineering Research Institute (NEERI), Maharashtra Pollution Control Board (MPCB) and Brihanmumbai Municipal Corporation (BMC). A monitoring station represents air quality at a particular location, while we need spatial variation for air quality management. Here, air quality monitored data of NEERI and BMC were spatially interpolated using various inbuilt interpolation techniques of ArcGIS. Inverse Distance Weight (IDW), Kriging (Spherical and Gaussian) and Spline techniques have been applied for spatial interpolation for this study. The interpolated results of air pollutants Sulpher dioxide (SO<sub>2</sub>), Nitrogen dioxide (NO<sub>2</sub>) and Suspended Particulate Matter (SPM) were compared with air quality data of MPCB in the same region. Comparison of results showed good agreement for predicted values using IDW and Kriging with observed data. Subsequently, health impact assessment of a ward was carried out based on total population of the ward and air quality monitored data within the ward. Finally, health cost within a ward was estimated on the basis of exposed population. This study helps to estimate the valuation of health damage due to air pollution.
Implication StatementOperating more number of air quality monitoring stations for measurement of air quality is highly resource intensive in terms of time and cost. The appropriate spatial interpolation techniques can be used to estimate concentration where air quality monitoring stations are not available. Further, health impact assessment for the population of the city and estimation of economic cost of health damage due to ambient air quality can help to make rational control strategies for environmental management. The total health cost for Mumbai city for the year 2012, with a population of 12.4 million, was estimated as 8000 million USD. Implication Statement Operating more number of air quality monitoring stations for measurement of air quality is highly resource intensive in terms of time and cost. The appropriate spatial interpolation techniques can be used to estimate concentration where air quality monitoring stations are not available. Further, health impact assessment for the population of the city and estimation of economic cost of health damage due to ambient air quality can help to make rational control strategies for environmental management. The total health cost for Mumbai city for the year 2012, with a population of 12.4 million, was estimated as 8000 million USD.