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Citation
Tags
HERO ID
3220205
Reference Type
Journal Article
Subtype
Review
Title
Review of receptor modeling methods for source apportionment
Author(s)
Hopke, PK
Year
2016
Is Peer Reviewed?
Yes
Journal
Journal of the Air and Waste Management Association
ISSN:
1096-2247
EISSN:
2162-2906
Volume
66
Issue
3
Page Numbers
237-259
Language
English
PMID
26756961
DOI
10.1080/10962247.2016.1140693
Web of Science Id
WOS:000371094300001
Abstract
UNLABELLED:
Efforts have been made to relate measured concentrations of airborne constituents to their origins for more than 50 years. During this time interval, there have been developments in the measurement technology to gather highly time-resolved, detailed chemical compositional data. Similarly, the improvements in computers have permitted a parallel development of data analysis tools that permit the extraction of information from these data. There is now a substantial capability to provide useful insights into the sources of pollutants and their atmospheric processing that can help inform air quality management options. Efforts have been made to combine receptor and chemical transport models to provide improved apportionments. Tools are available to utilize limited numbers of known profiles with the ambient data to obtain more accurate apportionments for targeted sources. In addition, tools are in place to allow more advanced models to be fitted to the data based on conceptual models of the nature of the sources and the sampling/analytical approach. Each of the approaches has its strengths and weaknesses. However, the field as a whole suffers from a lack of measurements of source emission compositions. There has not been an active effort to develop source profiles for stationary sources for a long time, and with many significant sources built in developing countries, the lack of local profiles is a serious problem in effective source apportionment. The field is now relatively mature in terms of its methods and its ability to adapt to new measurement technologies, so that we can be assured of a high likelihood of extracting the maximal information from the collected data.
IMPLICATIONS:
Efforts have been made over the past 50 years to use air quality data to estimate the influence of air pollution sources. These methods are now relatively mature and many are readily accessible through publically available software. This review examines the development of receptor models and the current state of the art in extracting source identification and apportionments from ambient air quality data.
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