Nicklin, Daniel and GOHARI DARABKHANI, Hamidreza (2021) Techniques to measure particulate matter emissions from stationary sources: A critical technology review using Multi Criteria Decision Analysis (MCDA). Journal of Environmental Management, 296 (113167). ISSN 0301-4797
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Abstract or description
This review article presents an overview of the commercially available methods to measure particulate matter (PM) from stationary sources, focusing on techniques to measure mass concentration. Mass concentration is the requirement for the majority of current regulations not only in the UK and Europe but also Worldwide. The process of particulate emission monitoring has been used and developed over the last 30 years as a result of increasing demands of legislation development and clean air initiatives. When deciding upon the measurement technique, the operator must consider; range of device, portability, usability, installation requirements, expected concentration, purpose of measurement, particle characteristics, cost and diameter of stack. This review aims to; give direction to operators looking for a measurement technique to measure mass concentration of particulate matter emissions, give direction to researchers working within the field of particulate measurement with a view to improving existing and developing new techniques and give strategy for selection of equipment. A literature review, industrial survey and Multi Criteria Decision Analysis (MCDA) were used for comprehensive analysis of nine measurement techniques operating in a full range of applications, highlighting the importance of matching a suitable device with the intended application. There is currently no suitable method available to measure mass both directly and continuously, resulting in using either the Standard Reference Method (SRM) or a continuous particulate monitor which requires calibration to its application using the SRM to obtain meaningful results. There is currently no single continuous particulate monitor available suitable for all applications.
Item Type: | Article |
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Faculty: | School of Digital, Technologies and Arts > Engineering |
Depositing User: | Hamidreza GOHARI DARABKHANI |
Date Deposited: | 29 Apr 2025 14:24 |
Last Modified: | 29 Apr 2025 14:24 |
Related URLs: | |
URI: | https://eprints.staffs.ac.uk/id/eprint/8966 |