ABSTRACT
Stable atmospheric boundary layer is conducive to the accumulation of atmospheric pollution and the occurrence of fog, and fog has a removal effect on air pollution. In this study, we use the observation and WRF-Chem (Weather Research and Forecasting Model with Chemistry) simulation to analyze the factors affecting the removal efficiency in a continuous fog and haze episode from November 26 to 28, 2018 in Jiangsu Province, such as fog thickness and duration. The results show that the WRF-Chem simulation well reproduces the boundary layer characteristics in the stages of fog formation, development and dissipation. The atmospheric boundary layer provides favorable conditions for the maintenance of fog and air pollution. The inversion layer, with the maximum intensity of 3 °C per 100 m, creates favorable thermal conditions, and the water vapor advection is also conducive to the fog maintenance. The ground observation verifies the wet scavenging of PM2.5 during dense fog events. The scavenging effect is related to the fog duration, and the correlation is positive when the fog is just formed and negative when the fog is dissipating. The PM2.5 concentration decreases from 159 µg m-3 to 38 µg m-3 after the fog lasts for 11 h. The fog has a remarkable scavenging effect on PM2.5 in the vertical direction, due to the deposition effect of fog droplets on the pollutant particles. The PM2.5 concentration on the ground is lower than the vertical average in the fog area, and the scavenging effects during the dense fog periods on November 27 and 28 are 47.7 µg m-3 and 36.1 µg m-3, respectively. The fog duration is mostly concentrated in 3-17 h. When the duration of fog is 4-8 h, the scavenging effect on PM2.5 reaches the strongest, with an average PM2.5 concentration decrease of >70 µg m-3.
ABSTRACT
This paper determined the delta 13C annual series of three Cryptomeria fortunei tree rings at West Tianmu Mountain, and analyzed their similarities and differences. In the period of 1837 to approximately 1982, the correlations among the three delta 13C series were significant, with r12 = 0.47, r13 = 0.65 and r23 = 0.52 (P < 0.001, n = 146), respectively. After removing the high-frequencies from the original delta 13C series by using polynomial function model, a significant correlation was observed among three low-frequencies, with the correlation coefficient varied from 0. 95 to 0.998. A significant correlation was also observed between original low-frequencies and simulated high-frequencies, with the correlation coefficient being 0.79 to approximately 0.84. The three delta 13C annual series had similar high-frequency and low-frequency variations. High-frequency variation recorded similar climate variation information, while low-frequency reflected the information of atmospheric CO2 changes. It was the common case for different individuals of trees that in the three delta 13C annual series, climatic factors caused high-frequency change, while atmospheric CO2 concentration caused low-frequency variation. The differences among the three delta 13C annual series were mainly caused by the local environmental conditions at the growth sites of trees, while the individual difference among the three delta 13C series caused by local environmental conditions had very small effects on the changes of the three delta 13C series. It could be concluded that the differences among the three delta 13C series did not affect the suitability of using tree ring's delta 13C annual series as the indirect evidence in climatic variation study, and the reliability and coherence of reconstructing historical climate changes.
