Air Quality Information Systems and geoss: Applications to India


Specific roles of each project team member



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Specific roles of each project team member


The collaborative team for this project has come together through previous and ongoing collaborations within the GEOSS Architecture Implementation Pilot, the Federation of Earth Science Information Partners (ESIP), McDonnell Academy Global Energy and Environment Partnership (MAGEEP), and other interactions. The project team is diverse with members bringing deep expertise across the spectrum of air quality science and management, monitoring, modeling, data analysis, knowledge of the Indian air quality programs and systems, and GEOSS information infrastructure. Together the group represents a subset of the air quality community that can connect activities across community building, decision support and infrastructure development to achieve a functioning and reusable framework that can serve as an exemplar for GEO in advancing its international objectives.

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, Modeling, data grid and DSS development, hosting database and DSS, training

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 to working with GEO to identify potential sponsors of this work. Once sponsors are identified, detailed budgets can be generated along with a more targeted project scope.

The table below is a summary of the costs associated with the effort. Appendix E includes a more detailed table that outlines each of these costs for each of the project collaborator institutions. Appendix E also includes a 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.

In estimating our overall budget each organization provided estimates for their anticipated labor associated with the project activities in community building (including workshops and training), air quality characterization and assessment, travel domestically and between the US and India, and information infrastructure development, including data web services and analytical tools. The estimates were provided with the understanding that once funding agencies were identified, a more formal budget exercise could be undertaken directed at more refined decision support requirements as they are expected to be defined in the coming months through the evolving IAQ-CoP.


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