Skip to main content

Receptor Modeling for Air Quality Management

  • 1st Edition, Volume 7 - June 3, 1991
  • Editor: P.K. Hopke
  • Language: English
  • eBook ISBN:
    9 7 8 - 0 - 0 8 - 0 8 6 8 3 4 - 9

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,… Read more

Receptor Modeling for Air Quality Management

Purchase options

LIMITED OFFER

Save 50% on book bundles

Immediately download your ebook while waiting for your print delivery. No promo code needed.

Image of books

Institutional subscription on ScienceDirect

Request a sales quote
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.