Names and contact information for each project team member
Project team members are listed alphabetically by last name.
Stefan Falke, Department of Energy, Environmental and Chemical Engineering, Washington University in St. Louis, Box 1180, St. Louis, Missouri 63130 USA stefan@wustl.edu
Rudolf Husar, Department of Energy, Environmental and Chemical Engineering, Washington University in St. Louis, Box 1180, St. Louis, Missouri 63130 USA rhusar@wustl.edu
Akshara Kaginalkar, Centre for Development of Advanced Computing, Sc&Eng Computing Group, Pune, INDIA akshara@cdac.in
Rakesh Kumar, Mumbai Zonal Center, National Environmental Engineering Research Institute, 89B, Dr.A.B.Road, Worli, Mumbai-400 018, INDIA r_kumar@neeri.res.in; rakeshmee@rediffmail.com (91) 98 208 39821
Shawn McClure, Colorado State Univ. – Cooperative Institute for Research in the Atmosphere, 1375 Campus Delivery, Fort Collins, CO 80523-1375, USA
Rashmi S. Patil, Centre for Environmental Science and Engineering, IIT Bombay, Powai, Mumbai 400 076, INDIA rspatil@iitb.ac.in (91) 22 2576 7858, (91) 98 209 10299
Ana Prados, University of Maryland Baltimore County, 5523 Research Park Drive, Baltimore MD 21228 aprados@umbc.edu
Virendra Sethi, Centre for Environmental Science and Engineering, IIT Bombay, Powai, Mumbai 400 076, INDIA vsethi@iitb.ac.in, (91) 98 207 87 567, (91) 22 2576 7851
Uma Shankar, Institute for the Environment, The University of North Carolina at Chapel Hill, Bank of America Plaza, CB # 6116, 137 E. Franklin St., Room 644, Chapel Hill, NC 27514, USA
M.P. Singh, Ansal Institute of Technology, Sector 55, Gurgaon, Haryana, 122003 INDIA director@aitgurgaon.org, (91) 99715 11455, (91) 124 411 6493
Chandra Venkataraman, Department of Chemical Engineering, IIT Bombay, Powai, Mumbai 400 076, INDIA chandra@iitb.ac.in, (91) 22 2576 7224
A.K. Yadav, Ansal Institute of Technology, Sector 55, Gurgaon, Haryana, 122003 INDIA akyadav@aitgurgaon.org, (91) 98715 92061, (91) 124 4750 502
Description of decision or problem needing improvement
It is now well accepted among the air quality management community in India that there is a need for science based tools to support decision making during the formulation of action plans leading to improved air quality. This has been motivated more so because recent decisions based on short term or limited data spectrum have not proved adequate for providing sustained solutions for air quality management. Many cities in the country have shown high levels of pollutants and do not meet the norms (UNEP, 2001). Further, sixteen most polluted cities were noted by the Indian Supreme Court and were directed to make air quality management action plans. Subsequently, Ministry of Environment and Forests (MoEF) listed 53 cities as polluted urban areas for which action plan was needed.
In a recent initiative of the Ministry of Environment and Forests, a Comprehensive Environmental Pollution Index (CEPI) has been developed (CPCB, 2009) and used for 88 industrial clusters spread across India. This index accounts for the levels of air pollution in these clusters. The choice of these industrial clusters is also partially based on their proximity to urban region, with risk of exposure in such high population areas. In another effort, the results from recently completed 6-city air pollution source apportionment studies (CPCB, 2010), underscores a national need for a system to continuously monitor, assess and develop action plans for improving the air quality in Indian cities.
Most of these efforts are need based, and often sporadic in nature. The accessibility for decision makers to have a holistic understanding of the air quality issues in a region is limited by factors such as lack of availability of air quality data, scattered data sources, and absence of time series data. For example, the estimation of the CEPI is a dynamic, as well as ongoing process and needs continuous flow of additional data and information for assessment and analyses for appropriate and prudent decision making.
Further, there is no robust structure or a platform for the air quality community to participate and share research, education and practices. For example, a level of capacity was built in India through the 6-city source apportionment study (funded by CPCB) [REF?/URL?]. However, in the absence of such a community, the activity ended abruptly from want of a vision and commitment for sustained efforts towards long term air quality management.
The proposed project is expected to be a leap-frogging activity for the Indian air quality management practices. This project shall lead to:
-
Creation of a dynamic and interoperable, distributed data network where multiple earth observations (such as ground, satellite and model based) related to air quality are catalogued for easy access, visualization and analysis over dimensions of spatial, temporal and nature of pollutants.
-
Use and understanding of tools and services within the GEOSS infrastructure will lead to immense benefit to air quality managers and researchers in the country.
-
Developing some of the viable activities under this system such as, emission source identification, exceptional event analyses, forecasting, assessment of air quality scenarios and identification of air pollution hot spots in the country.
-
Integrating the AQ-COP of India with others for further strengthening of knowledge in India and elsewhere.
-
Providing a window to learn and take action as also see the effect of the action and improve the methodologies for future decisions.
-
Further, this would be accomplished through evolution of a community of practice for air quality in India.
Technical/Management Section Background of Air Quality Monitoring in India
The Central Pollution Control Board (CPCB) and State Pollution Control Boards (SPCBs) are the government agencies responsible for managing air quality at national and state levels. The ground based monitoring networks in India include the National Ambient Monitoring Programme (NAMP) network operated under the guidelines of Central Pollution Control Board, state level air monitoring networks operated by respective State Pollution Control Boards, and other networks operated by the National Environmental Engineering Research Institute (NEERI), universities and research groups. Studies on the health impact of air pollution in India have been limited and the high pollution levels in a large number of cities with high population densities are a cause for concern. An example issue in need of improved decision support tools and technologies is the impact on crops due to ozone and climate change, including early warning systems and public service bulletins to targeted communities.
The NAMP network consists of 342 operating stations within 127 cities in 26 states and 4 Union Territories of the country. All these stations monitor sulfur dioxide (SO2), nitrogen dioxide (NO2), Respirable Suspended Particulate Matter (RSPM) and Suspended Particulate Matter (SPM) ), Ammonia and Hydrogen Sulphide on every third day. More than 100 continuous monitoring stations have been also commissioned by CPCB, SPCB’s and the Industry in cities of concern such as Mumbai, Delhi, Pune etc. Periodically, heavy metals in PM and PAHs are also analyzed from many of these stations.
Major Issues with Air Quality Monitoring System
The present system of measurement does serve a purpose of providing city specific plan however, it has limited role in terms of understanding of little extended region around these cities. The point measurements from the monitoring stations are thus limited in their temporal frequency and geographic coverage, and lack the spatial continuity to provide a synoptic view of air quality in the region. The current monitoring network also lacks monitoring in rural areas that are impacted by pollution transport downwind of urban and industrialized areas. The other related problem is with regard to data of background against which the cities air quality can be compared. The background data points are very limited compared to urban centric or industrial clusters data from monitoring stations. With the addition of continuous monitoring stations is some cities, issue pertaining to inter-comparison of data within the cities as also across the country, becomes a major concern.
Responses needed
Additional modes of monitoring are needed to better assess air quality and recent developments in the earth observation (EO) systems provide an excellent opportunity to integrate satellite data with surface measurements to support the decision-making processes for effective air quality management. Presently, these data are not utilized to their full potential for air quality management in India, and are, for the most part, limited to the research community. The opportunity to find, access and understand air quality data from different sources for examining, processing, overlaying and displaying would offer an added dimension to the air quality management processes in the country.
The GEOSS vision provides a structure for environmental data to be easily available through an interoperability framework that allows them to be used via various subsets and combinations in support specific research and decision applications (Figure 1).
Figure 1: GEOSS connecting observation and modeling systems with decision processes
The use of data and their application for air quality achieved in GEOSS through web and data standards would allow disparate data to be accessible to a variety of decision support tools. The GEOSS Common Infrastructure (GCI) on one hand would provide a channel for data providers to register and catalog standards-based web service interfaces to satellite, surface and modeled data, and on the other hand, for data consumers to find and access those data.
The atmospheric composition over India is determined by the sources within India as well as by the contributions from neighboring regions. A full air quality characterization requires a multi-scale approach, consisting of global, regional/national and local perspectives as depicted in Figure 2. Global data, analyses and models provide the broad geographic and chemical pattern and visualize pollutant transport into and out of the Indian sub-continent. Surface observations are inherently local and the analysis of local conditions is necessary for the full understanding of air quality, particularly in mega-cities and industrial areas. Air quality monitoring networks managed by the Indian national agencies provide important observation data that can be augmented with satellite data and model results.
It is anticipated that a key contribution of the proposed project will be the India-scale characterization of air quality facilitated by the Indian and GEOSS Air Quality Communities of Practice (AQ CoPs). The regional/India-scale observations, analyses and modeling results can be synthesized from the combination of global observations provided by the GEO AQ CoP and national observations within India.
Figure 2. Multi-scale perspective needed for AQ characterization
This proposal focuses on strengthening and developing new capabilities for Indian air quality management activities, which has ample intellectual capacity to benefit from such infusion in a few key areas, and which could be expected to carry the program forward operationally on its own in approximately 3-4 years. This is a reasonable estimate for the development of a prototype system that is ready to be transitioned into an operational system for routine applications based on experience in related projects to develop air quality decision support systems in the U.S.
Dostları ilə paylaş: |