Abstract
In this paper, a 3D sonic anemometer and two optical particulate sensors were used to observe fugitive particulate matter 10 μm (PM10) emission from the coal storage yard of a thermal power plant for one month. The PM10 emission flux was calculated using the flux gradient method. The results show that the heat flux, convective velocity, and PM10 emission flux have obvious diurnal variation. The PM10 emission flux is positively correlated with heat flux, convective velocity, and frictional velocity, but negatively correlated with humidity. Based on the convective velocity, friction velocity and humidity as the independent variables, a multivariate regression model of PM10 emission flux was constructed. The prediction results of the model are in good agreement with the experimental values. The emission flux of PM10 can also be estimated quasi-quantitatively according to the value of gradient Richardson number (Ri). There are two time windows for PM10 emissions, namely the discharge window period (9:00–20:00) and the static window period (20:00–9:00 of next day).In order to reduce PM10 emissions more effectively, artificial climate intervention such as watering, spraying, and other measures should be carried out during the discharge window period. Studies have shown that the flux gradient method can be successfully used to accurately measure the PM10 emission flux of a coal storage yard. This study also provides useful recommendations for real-time monitoring and controlling PM10 emissions from coal storage sites.
Published Version
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