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