| Literature DB >> 26753788 |
T Petäjä1,2, L Järvi1, V-M Kerminen1, A J Ding2, J N Sun2, W Nie1,2, J Kujansuu1, A Virkkula2,3, X-Q Yang2, C B Fu2, S Zilitinkevich1,3,4,5,6, M Kulmala1.
Abstract
Severe air pollution episodes have been frequent in China during the recent years. While high emissions are the primary reason for increasing pollutant concentrations, the ultimate cause for the most severe pollution episodes has remained unclear. Here we show that a high concentration of particulate matter (PM) will enhance the stability of an urban boundary layer, which in turn decreases the boundary layer height and consequently cause further increases in PM concentrations. We estimate the strength of this positive feedback mechanism by combining a new theoretical framework with ambient observations. We show that the feedback remains moderate at fine PM concentrations lower than about 200 μg m(-3), but that it becomes increasingly effective at higher PM loadings resulting from the combined effect of high surface PM emissions and massive secondary PM production within the boundary layer. Our analysis explains why air pollution episodes are particularly serious and severe in megacities and during the days when synoptic weather conditions stay constant.Entities:
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Year: 2016 PMID: 26753788 PMCID: PMC4709519 DOI: 10.1038/srep18998
Source DB: PubMed Journal: Sci Rep ISSN: 2045-2322 Impact factor: 4.379
Figure 1A schematic figure of the feedback mechanism initiated by the increased aerosol concentration in the boundary layer leading to lower boundary layer height and hence elevated aerosol concentrations.
Figure 2Time series of (a) fine aerosol particles (PM2.5) and black carbon (BC) mass concentrations, (b) solar radiation (Kdown) and relative humidity (RH), (c) wind speed (U) and direction (WD) and (d) the boundary layer height (h).
Figure 3Observed dependency of the ratio between the turbulent vertical flux (Fb) and the solar radiation at the top of the atmosphere (Ktop) as a function on observed particulate mass (PM2.5) concentration.
The fitting includes all the data points. To guide the eye, the PM2.5 data is binned in five batches where the median is shown as a line whereas the outer boundaries of the boxes represent 25 and 75 quartiles and the dashed lines present interquartile range (IQR). Dashed vertical lines represent 5 and 95 percentile ranges in each bin. Only daytime conditions between 10:00 and 14:00 local time from non-rainy periods are considered. Atmospheric RH during the measurements is indicated with the color of the data point. The dependency of the other radiation components are presented on PM2.5 is presented in Supplementary Fig. A1 and on BC concentration in Supplementary Fig. A2.
Figure 4The anticipated change in the ratio of polluted to non-polluted boundary layer heights separately for all the available data and for relative humidity below 80%.
The points present observational data. The color of the data points describe relative humidity with same classification as in Fig. 3. The solid lines present the fitted dependency and the dashed lines show the sensitivity of the results based on estimated fitting errors.