期刊
JOURNAL OF ENVIRONMENTAL SCIENCES
卷 48, 期 -, 页码 161-168出版社
SCIENCE PRESS
DOI: 10.1016/j.jes.2016.03.024
关键词
PM10 concentration; PM2.5 concentration estimation; Wind speed; Wind direction
资金
- National Science & Technology Major Program of China [2012CB955503]
- National Natural Science Foundation of China [41421001, 41301425, 41271404]
When investigating the impact of air pollution on health, particulate matter less than 2.5 mu m in aerodynamic diameter (PM2.5) is considered more harmful than particulates of other sizes. Therefore, studies of PM2.5 have attracted more attention. Beijing, the capital of China, is notorious for its serious air pollution problem, an issue which has been of great concern to the residents, government, and related institutes for decades. However, in China, significantly less time has been devoted to observing PM2.5 than for PM10. Especially before 2013, the density of the PM2.5 ground observation network was relatively low, and the distribution of observation stations was uneven. One solution is to estimate PM2.5 concentrations from the existing data on PM10. In the present study, by analyzing the relationship between the concentrations of PM2.5 and PM10, and the meteorological conditions for each season in Beijing from 2008 to 2014, a U-shaped relationship was found between the daily maximum wind speed and the daily PM concentration, including both PM2.5 and PM10. That is, the relationship between wind speed and PM concentration is not a simple positive or negative correlation in these wind directions; their relationship has a complex effect, with higher PM at low and high wind than for moderate winds. Additionally, in contrast to previous studies, we found that the PM2.5/PM10 ratio is proportional to the mean relative humidity (MRH). According to this relationship, for each season we established a multiple nonlinear regression (MNLR) model to estimate the PM2.5 concentrations of the missing periods. (C) 2016 The Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences. Published by Elsevier B.V.
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