A Reliable Data Collection And Control System Provided As A Service Within The Global Mercury Observation Network | 18560
Journal of Earth Science & Climatic Change
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The overall goal of the on-going Global Mercury Observation System (GMOS) project is to develop a coordinated observation
network on global scale for mercury, by integrating historical measurements across the globe with newly established
GMOS land-based sites in the Northern and Southern Hemisphere, at high altitude and sea level locations. The measurement
programme includes tropospheric measurements and oceanographic campaigns to provide a comprehensive assessment of
mercury concentrations in ambient air and deposition. To facilitate data sharing with major stakeholders, policymakers and
the public, an ad-hoc Cyber(e)-Infrastructure (CI) was developed.
The CI was designed to make data acquisition in near-real time, by apply advanced Information and Comunication
Technology (ICT) systems. To provide a common framework of analysis as well as a real-time control of instruments, a
dedicated GMOS-Data Quality Management system (G-DQM) was developed as a web-based service. G-DQM is able to
automatically screen and quality-control the incoming atmospheric mercury raw data allowing near-real time adaptive
monitoring procedures. Dealing with site-specific conditions and their related instrumental settings, the G-DQM system may
provide suitable feedback to all GMOS site operators.
The faithful application of the G-DQM system allows to identify the main frequent issues to be overcome for a reliable
atmospheric mercury data collection. The use of this system is of greatest usefulness in preventing the production of poor-
quality data and assuring comparability of different datasets recorded within the GMOS network
Francesco D'Amore is PhD on Computer Science. He has a post-doc position at CNR - Institute of Atmospheric Pollution Research (CNR-IIA), working on
e-Science, data harmonization and earth observation. His important works are related to the design and development of innovative Spatial Data Infrastructure,
which are oriented to data quality assurance and monitoring.
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