A Quantitative Modeling and Prediction Method for Sustained Rainfall-PM2.5 Removal Modes on a Micro-Temporal Scale

Abstract

PM2.5 is unanimously considered to be an important indicator of air quality. Sustained rainfall is a kind of typical but complex rainfall process in southern China with an uncertain duration and intervals. During sustained rainfall, the variation of PM2.5 concentrations in hour-level time series is diverse and complex. However, existing analytical methods mainly examine overall removals at the annual/monthly time scale, missing a quantitative analysis mode that applies micro-scale time data to describe the removal phenomenon. In order to further achieve air quality prediction and prevention in the short term, it is necessary to analyze its micro-temporal removal effect for atmospheric environment quality forecasting. This paper proposed a quantitative modeling and prediction method for sustained rainfall-PM2.5 removal modes on a micro-temporal scale. Firstly, a set of quantitative modes for sustained rainfall-PM2.5 removal mode in a micro-temporal scale were constructed. Then, a mode-constrained prediction of the sustained rainfall-PM2.5 removal effect using the factorization machines (FM) was proposed to predict the future sustained rainfall removal effect. Moreover, the historical observation data of Nanjing city at an hourly scale from 2016 to January 2020 were used for mode modeling. Meanwhile, the whole 2020 year observation data were used for the sustained rainfall-PM2.5 removal phenomenon prediction. The experiment shows the reasonableness and effectiveness of the proposed method.

Prediction and Comparative Analysis of the Influence of Magnetic Field Effect on PM2.5 Trapping Efficiency in Electrostatic Precipitator (ESP) under Different Temperatures

“…atures becomes smaller as the flue gas velocity increases, which shows that the temperature has less influence on the grade efficiency at high flue gas velocity. (5) In the presence or absence of a magnetic field, the higher the temperature, the lower the weakened gradient of the flue gas velocity on the grade efficiency, which suggests that the increase in temperature reduces the influence of the flue gas velocity on the grade efficiency. To gain a clearer understanding of the relationship between magnetic field and flue gas velocity, the grade efficiency with and without a magnetic field at 873 K and at different flue gas velocities can be obtained based on Figure 10, as shown in Figure 13: (1) At the same temperature, the difference in grade efficiency among different flue gas velocities gradually decreases and flattens with the increases in particle size, indicating that the magnetic field has a more pronounced effect on enhancing the grade efficiency of smaller particle sizes.…”

“…They found that the number of publications on PM2.5 exposure has been increasing at an accelerating rate. Wu et al [5] proposed a quantitative modeling and prediction method for sustained rainfall-PM2.5 removal modes on a micro-temporal scale, citing the reasonableness and effectiveness of the proposed method.…”