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Now revised and updated, the second edition of this book includes new topics including a look at pollution prevention, drinking water standards, volatile organic compounds, indoor air quality and emissions monitoring.
Munitions Response Site Prioritization Protocol (US Department of Defense Regulation) (DOD) (2018 Edition) The Law Library presents the complete text of the Munitions Response Site Prioritization Protocol (US Department of Defense Regulation) (DOD) (2018 Edition). Updated as of May 29, 2018 The Department of Defense (hereinafter the Department) is promulgating the Munitions Response Site (MRS) Prioritization Protocol (MRSPP) (hereinafter referred to as the rule) as a rule. This rule implements the requirement established in section 311(b) of the National Defense Authorization Act for Fiscal Year 2002 for the Department to assign a relative priority for munitions responses to each location (hereinafter MRS) in the Department's inventory of defense sites known or suspected of containing unexploded ordnance (UXO), discarded military munitions (DMM), or munitions constituents (MC). This book contains: - The complete text of the Munitions Response Site Prioritization Protocol (US Department of Defense Regulation) (DOD) (2018 Edition) - A table of contents with the page number of each section
Process and input-output analysis have emerged as the two principal methods of analyzing health risks of energy technologies. This book describes applications and differences between these two methods with discussions of sources or error and uncertainty, data limitations and some solutions to common problems. Its goals are to provide understanding of the strengths and weaknesses of the methods and to provide a basis for standardizing risk assessment for energy policy analysis. Sections of the book describe risk analysis and develop issues common to both the process and input-output methods, describe data bases and their limitations, discuss use of environmental models for generating environmental information not available in data bases, describe applications of the methods in case studies, and discuss the state-of-the-art of the two models and opportunities for combining them to take advantage of their relative strengths and weaknesses.