Review of Monitoring Methods for Submicronsized Particulates Emission in Coal-fired Power Plants
- DOI
- 10.2991/esm-16.2016.68How to use a DOI?
- Keywords
- Low concentration, test, high humidity, PM2.5, particulates
- Abstract
Particulates emission from coal-fired power plant is considered to be the main source of air pollutants. With the implementation of the new China national ambient air quality standard, monitoring and controlling particulate emission from coal-fired power plants are very important, and how to accurately measure the emission of particulate matters is the key point. There are two major challenges for monitoring methods: the determination of PM 10 and PM 2.5 emissions from coal-fired power plants and the measurement of the low concentration particulates in high humidity flue gas environment. Views of the above problems, all of the mainstream technologies for these two difficulties are reviewed in this paper, and both advantages and disadvantages of these methods are discussed as well. The result shows that: in high humidity flue gas, the relative accurate results of particulates concentration can be obtained by membrane filter method. Additionally, the direct sampling method of fine particulate matter based on source environment was widely used in daily monitoring and it can basically meet the needs of classification detection of fine particles in coal-fired power plant.
- Copyright
- © 2016, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Yiwei Chen AU - Gengda Li AU - Zhenxin Sun AU - Hua Guo AU - Hanqiang Liu AU - Haoran Chen AU - Shuming Du AU - Yang Yang PY - 2016/08 DA - 2016/08 TI - Review of Monitoring Methods for Submicronsized Particulates Emission in Coal-fired Power Plants BT - Proceedings of the 2016 International Conference on Engineering Science and Management PB - Atlantis Press SP - 291 EP - 299 SN - 2352-5401 UR - https://doi.org/10.2991/esm-16.2016.68 DO - 10.2991/esm-16.2016.68 ID - Chen2016/08 ER -