TY - JOUR
T1 - Impact of synoptic patterns and meteorological elements on the wintertime haze in the Beijing-Tianjin-Hebei region, China from 2013 to 2017
AU - Bei, Naifang
AU - Li, Xiaopei
AU - Tie, Xuexi
AU - Zhao, Linna
AU - Wu, Jiarui
AU - Li, Xia
AU - Liu, Lang
AU - Shen, Zhenxing
AU - Li, Guohui
N1 - Publisher Copyright:
© 2019 Elsevier B.V.
PY - 2020/2/20
Y1 - 2020/2/20
N2 - Meteorological conditions play a key role in formation of air pollution, determining dispersion or accumulation of air pollutants. Aggressive emission mitigation measures have been taken recently in the Beijing-Tianjin-Hebei region (BTH), China, but pervasive and persistent haze still frequently engulfs this region during wintertime. Occurrence frequency of unfavorable meteorological conditions in winter is anticipated to constitute a significantly important factor in driving the heavy haze formation in BTH. Large scale synoptic patterns influencing BTH during the wintertime from 2013 to 2017 are categorized into six types, including “north-low”, “southwest-trough”, “southeast-high”, “southeast-trough”, “transition”, and “inland-high” using the NCEP reanalysis data. “Southwest-trough” and “southeast-high” are defined as favorable synoptic patterns and the remaining four categories are unfavorable ones based on FLEXPART simulations. Compared to measurements of fine particulate matter (PM2.5) in BTH, favorable synoptic conditions generally correspond to the low level or decreasing trend of PM2.5 concentrations while under unfavorable conditions PM2.5 concentrations are high or increasing. Occurrence of wintertime haze episodes in BTH correlates well with the evolution trend of unfavorable synoptic patterns from 2013 to 2017 although the anthropogenic emissions have substantially decreased. PM2.5 concentrations also exhibit correlations with local meteorological elements, including winds, temperature, and relative humidity, which are ultimately steered by large scale synoptic situations. The WRF-Chem model simulations further reveal the critical role of large-scale synoptic patterns in the heavy haze formation. Overall, under unfavorable synoptic situations, emission mitigation is the best choice to improve the air quality in BTH.
AB - Meteorological conditions play a key role in formation of air pollution, determining dispersion or accumulation of air pollutants. Aggressive emission mitigation measures have been taken recently in the Beijing-Tianjin-Hebei region (BTH), China, but pervasive and persistent haze still frequently engulfs this region during wintertime. Occurrence frequency of unfavorable meteorological conditions in winter is anticipated to constitute a significantly important factor in driving the heavy haze formation in BTH. Large scale synoptic patterns influencing BTH during the wintertime from 2013 to 2017 are categorized into six types, including “north-low”, “southwest-trough”, “southeast-high”, “southeast-trough”, “transition”, and “inland-high” using the NCEP reanalysis data. “Southwest-trough” and “southeast-high” are defined as favorable synoptic patterns and the remaining four categories are unfavorable ones based on FLEXPART simulations. Compared to measurements of fine particulate matter (PM2.5) in BTH, favorable synoptic conditions generally correspond to the low level or decreasing trend of PM2.5 concentrations while under unfavorable conditions PM2.5 concentrations are high or increasing. Occurrence of wintertime haze episodes in BTH correlates well with the evolution trend of unfavorable synoptic patterns from 2013 to 2017 although the anthropogenic emissions have substantially decreased. PM2.5 concentrations also exhibit correlations with local meteorological elements, including winds, temperature, and relative humidity, which are ultimately steered by large scale synoptic situations. The WRF-Chem model simulations further reveal the critical role of large-scale synoptic patterns in the heavy haze formation. Overall, under unfavorable synoptic situations, emission mitigation is the best choice to improve the air quality in BTH.
KW - BTH
KW - PM
KW - Synoptic situations
UR - https://www.scopus.com/pages/publications/85075973677
U2 - 10.1016/j.scitotenv.2019.135210
DO - 10.1016/j.scitotenv.2019.135210
M3 - 文章
C2 - 31821922
AN - SCOPUS:85075973677
SN - 0048-9697
VL - 704
JO - Science of the Total Environment
JF - Science of the Total Environment
M1 - 135210
ER -