Improvement of data quality for post-closure care of landfills using a tiered decision matrix approach case studies

The development of a systematic approach which can be used as a decision-making tool to extend or shorten the post-closure care (PCC) period requires technically sound and justifiable methods. These methods can incorporate analysis and interpretation of available data and information from closed lan...

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Veröffentlicht in:Waste management & research : the journal of the International Solid Wastes and Public Cleansing Association, ISWA. - 1991. - 30(2012), 2 vom: 01. Feb., Seite 171-80
1. Verfasser: Sizirici, Banu (VerfasserIn)
Weitere Verfasser: Tansel, Berrin
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2012
Zugriff auf das übergeordnete Werk:Waste management & research : the journal of the International Solid Wastes and Public Cleansing Association, ISWA
Schlagworte:Journal Article Research Support, Non-U.S. Gov't
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520 |a The development of a systematic approach which can be used as a decision-making tool to extend or shorten the post-closure care (PCC) period requires technically sound and justifiable methods. These methods can incorporate analysis and interpretation of available data and information from closed landfill. Analysis of existing data from closed landfills may present challenges due to variations in the data collection procedures, data analysis methods and reporting methodologies used during active and post-closure periods of a landfill. A tiered decision matrix was developed to assess and verify the quality of monitoring data collected and documented from closed landfills. The matrix provides a baseline for the needs to improve the quality of data collection and documentation for current and future practices. Challenges due to discrepancies in data reporting and inconsistencies in quality assurance/quality control protocols during data collection, reporting, and analyses are presented with case studies. Solutions are presented to validate and improve the quality of available data based on this study 
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