Particulate air pollution data for Coimbatore, India: real time monitoring and modeling with data-interoperability measures

Particulate air pollution is a major health burden and environmental concern in urban areas. As
a serious health problem in urban areas, current intervention measures has to be sufficiently
refined for urgent and sustainable management. Data intensive approach can gives tools
to integrate diverse data sources for deriving decision-making information and improved
applications for adaptive management of pollution. However lack of spatio-temporally relevant
and reliable data on particulate pollution and the data existing in non-interoperable formats to a
great extent hampers knowledge generation for effective control of pollution and management
of air quality.
The current study focused on developing basic tools for data intensive approach in a second
tier urban centre of India. The study intends to explore an affordable real time air quality
information systems focusing on Coimbatore, a fast growing and second tier urban center in
the state of Tamil Nadu, India and its surroundings as the study area. The major objectives of
the study were (1) to develop a real time particulate pollution monitoring system using low
cost commodity sensors and assess its effectiveness in the study area, (2) attempt a real time
particulate pollution modeling system for the study area using WRF-CHEM, addressing its
computational requirements, and (3) demonstrate application of interoperability measures on
real time particulate pollution data.
To address the first objective, a real time particulate monitor was developed by integrating
off-the-shelf indoor dust sensors with an appropriately customized data communication system.
To address the objective two, as an essential data requirement for WRF-CHEM modeling,
particulate matter (PM 2.5 and PM 10 ) emission inventory was prepared for the study area. 
Programming tools (codes) were developed for remote computing based real time execution
and evaluation of model performance over the study area using the developed emission inventory.
Objective three of the study was addressed using sensor web enablement specification and
its application. Web based data dissemination and application of statistical analysis tools
were used to demonstrate the advantages of interoperability measures on real time particulate
pollution data in the study area.