Air Quality Information Systems and geoss: Applications to India

Specific roles of each project team member

The collaborative team for this project has come together through previous collaborations within the GEOSS Architecture Implementation Pilot Phase-2 (AIP-2), the Federation of Earth Science Information Partners (ESIP), McDonnell Academy Global Energy and Environment Partnership (MAGEEP), and other interactions.

Name	Organization	Role
Stefan Falke	Washington University	Co-PI (Point-Of-Contact), Project coordination, GEOSS Common Infrastructure, collaborative analytical tools
Uma Shankar	University of North Carolina	Co-PI, Modeling, training
Virendra Sethi	IIT Bombay	Co-PI, Community building, India air quality monitoring and data, application to decision processes
Rudolf Husar	Washington University	Co-PI, Multi-data source air quality characterization, GEOSS Infrastructure
Rakesh Kumar	National Environmental Engineering Research Institute	Co-I, Air Quality Monitoring and Decision Support System for Air quality Management decisions, Economic analysis, Technology issues of air pollution control
Chandra Venkataraman	IIT Bombay	Co-I, Modeling, India regional-scale emissions inventory, model inter-comparisons
Ana Prados	University of Maryland – Baltimore County	Co-I, Satellite data for air quality analysis, training
Akshara Kaginalkar	Centre for Development of Advanced Computing	Co-I,
Shawn McClure	Colorado State University	Co-I, Web services, analysis tools
Rashmi S. Patil	IIT Bombay	Co-I, Air Quality Modelling and Measurements
M.P. Singh	Ansal Institute of Technology	Co-I, Conducting modeling studies, dissemination through training, workshops and conferences
A.K. Yadav	Ansal Institute of Technology	Co-I, Air Quality Characterization and analysis, training workshops
Erin Robinson	Washington University	GEOSS Common Infrastructure and Air quality community infrastructure
Ratish Menon	IIT Bombay	Air quality characterization methods
Kari Hoijarvi	Washington University	Web developer

Project budget (estimated)

The following represents a budget estimate for the proposed work. They are intended as a ball-park figure and to indicate the budget distribution across collaborators and project activities. We look forward in working with GEO to identify potential sponsors of this work. Once sponsors are identified, detailed budgets will be generated and finalized. Please refer to Appendix D for detailed breakdown of US organization budget estimates along with budget justifications. For contractual purposes for the US organizations, Washington University in St. Louis will serve as the PI institution.

Project schedule

Assuming adequate levels of support for the project team, we plan for a 4-year effort in 5 partially overlapping phases. A key milestone occurs in the later half of year 3 with a demonstration of the integrated approach to air quality characterization. For planning purposes, the overall project period is 1 January 2011 – 31 Dec 2014.

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  Phase 1 (~ 9 months)
  
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    Phase 1a (~9 months) - community building, engaging stakeholders and partners and identifying available data for the use in the prototype and where those data nodes will be maintained for the India air quality network
    
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    Phase1b (~3 months) - identify existing data resources and make available for project
    
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  Phase 2 (~18 months) - create and test standard web service interfaces to the data and in ensuring access to already existing services, and the registration of the services in an air quality community web catalog connected with the GEOSS Common Infrastructure (GCI) and the necessary interfaces to decision support tools
  
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  Phase 3 (~18 months) - application development using GCI and coordination with decision support processes in air quality characterization
  
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  Phase 4 (~6 months) - demonstration of prototype GEOSS Air Quality Applications for India to multiple air quality audiences and conducting workshops for learning how to work with the air quality infrastructure, multiple sources of data, and analytical tools
  
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  Phase 5 (~12 months) Refine the prototype analysis system based on feedback from demonstrations and workshops and develop a plan to transition to an operational status.