Receptor Modeling for Air Quality Management, Volume 7 (Data Handling in Science and Technology)

Hopke, P.K.

ISBN 10: 0444882189 / ISBN 13: 9780444882189

Editore: Elsevier Science (edition 1), 1991

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It's a preowned item in good condition and includes all the pages. It may have some general signs of wear and tear, such as markings, highlighting, slight damage to the cover, minimal wear to the binding, etc., but they will not affect the overall reading experience.

Codice articolo 0444882189-11-1

Dati bibliografici

• Titolo: Receptor Modeling for Air Quality Management, Volume 7 (Data Handling in Science and Technology)
• Editore: Elsevier Science (edition 1)
• Data di pubblicazione: 1991
• Lingua: Inglese
• ISBN 10: 0444882189
• ISBN 13: 9780444882189
• Rilegatura: Hardcover
• Edizione: 1.
• Condizione: Good

Descrizione articolo

Riassunto

This book presents the background and application of receptor models for the source identification and quantitative mass apportionment of airborne pollutants. Over the past decade, receptor models have become an accepted part of the process for developing effective and efficient air quality management plans. Information is provided on the ambient and source sampling and chemical analysis needed to provide the input data for receptor models. Commonly used models are described with examples so that the air quality specialist can see how these models are applied. Recent advances in several areas of the field are presented as well as the perspective of both U.S. Federal and State level air quality managers on how these models fit into the development of a management plan.

The aim of the book is to provide a practical guide to persons who may be given the task of implementing receptor modeling as a part of some air quality management problem. The intention of all the chapter authors is to furnish both the basic information needed to begin doing receptor modeling as well as some insight into some of the problems related to the use of these models. These tools like any others used in solving complex technological problems are not a panacea, but do represent powerful aids in data analysis that can lead to insights as to how an airshed functions and thus, to effective and efficient air quality management strategies.