A study of winter haze pollution over a rural area of central Northern China Plain based on satellite and surface observations
WANG Xin-hui1,2, SU Lin1, TAO Ming-hui1, WANG Zi-feng1, CHEN Liang-fu1, LI Shen-shen1, WANG Yang1,2
1. State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, China Academy of Sciences, Beijing 100101, China;
2. University of China Academy of Sciences, Beijing 100049, China
This paper employed ground-based measurements, multiple satellite observations, NCEP reanalysis data, meteorological sounding data and Modeled HYSPLIT4backward trajectory results to analyse the pollution characteristics and forming process of haze pollution in Zhongmou, a rural site located in the central North China Plain. The Comprehensive observation campaign lasted from December 13th, 2014 to January 16th, 2015 and a total of five haze pollution episodes were captured Haze days accounted for 82% of the total number of days, while heavily polluted days (Class V and VI based on AQI level) accounted for 46%. The ground-based observations showed that: 1) the concentrations of PM and SO2, NOx were highly correlated, 2) fine particulate matters were dominant among the ground-level pollutants, 3) and the secondary aerosols transformed from gaseous pollutants accounted for a predominant fraction of fine particles. CALIPSO and AMPLE vertical detection data showed that thick haze clouds were dominated by floating dust in the middle and upper layer, and coarse dust particles were prevalent over North China Plain, which accounted for a predominant fraction in the columnar optical volume. Based on meteorological sounding data, the atmospheric stratification of the planetary boundary layer (PBL) was stable, suppressing air turbulence in PBL and favoring formation and maintenance of haze. Meteorological data also showed that near-ground wind speed and direction had a great influence on haze maintenance and dissipation; High-level wind field data indicated that the first haze was influenced by floating dust from the northwest, and the fifth episode was influenced by water vapor from the south. By tracking the 100m air mass using HYSPLIY4model, the low-altitude pollutants were transported from northwest and northeast. The contribution from northeast, accounting for almost 14%, passed Hebei and Shandong province, while short distance transportation traces were mostly from Zhengzhou and Luoyang, accounting for almost 33%.
王新辉, 苏林, 陶明辉, 王子峰, 陈良富, 李莘莘, 汪洋. 基于星地同步观测的华北平原中部背景地区冬季霾污染过程[J]. 中国环境科学, 2016, 36(6): 1610-1620.
WANG Xin-hui, SU Lin, TAO Ming-hui, WANG Zi-feng, CHEN Liang-fu, LI Shen-shen, WANG Yang. A study of winter haze pollution over a rural area of central Northern China Plain based on satellite and surface observations. CHINA ENVIRONMENTAL SCIENCECE, 2016, 36(6): 1610-1620.
Ma J, ZWang W, Chen Y, et al. The IPAC-NC field campaign: a pollution and oxidization pool in the lower atmosphere over Huabei, China [J]. Atmospheric Chemistry and Physics, 2012, 12(9):3883-3908.
[4]
Tao M, Chen L, Su L, et al. Satellite observation of regional haze pollution over the North China Plain [J]. Journal of Geophysical Research: Atmospheres (1984~2012), 2012, 117(D12), DOI:10. 1029/2012JD017915.
[5]
Ji D, Wang Y, Wang L, et al. Analysis of heavy pollution episodes in selected cities of northern China [J]. Atmospheric Environment, 2012(50):338-348.
[6]
Andreae M O, Browell E V, Garstang M, et al. Biomass-burning emissions and associated haze layers over Amazonia [J]. Journal of Geophysical Research, 1988,93(D2):1509-1527.
[7]
Okada K, Ikegami M, Zaizen Y, et al. The mixture state of individual aerosol particles in the 1997 Indonesian haze episode [J]. J Aerosol Sci., 2001(32):1269-1279.
[8]
Whiteaker J R, Suess D T, Prather K A. Effects of meteorological conditions on aerosol composition and mixing state in Bakersfield, CA [J]. Environmental Science & Technology, 2002,36(11):2345-2353.
Zhang X Y, Wang Y Q, Niu T, et al. Atmospheric aerosol compositions in China: spatial/temporal variability, chemical signature, regional haze distribution and comparisons with global aerosols [J]. Atmospheric Chemistry and Physics, 2012,12(2): 779-799.
Huang K, Zhuang G, Fu J S et al. Typical types and formation mechanisms of haze in an Eastern Asia megacity, Shanghai [J]. Atmospheric Chemistry and Physics, 2012,12(1):105-124.
[14]
Jung J, Lee H, Kim Y J, et al. Optical properties of atmospheric aerosols obtained by in situ and remote measurements during 2006 Campaign of Air Quality Research in Beijing (CAREBeijing-2006) [J]. Journal of Geophysical Research: Atmospheres (1984-2012), 2009,114(D2), DOI:10.1029/ 2008JD010337.
Tao M, Chen L, Wang Z, et al. A study of urban pollution and haze clouds over northern China during the dusty season based on satellite and surface observations [J]. Atmospheric Environment, 2014,82:183-192.
[19]
Hänel A, Baars H, Althausen D, et al. One-year aerosol profiling with EUCAARI Raman lidar at Shangdianzi GAW station: Beijing plume and seasonal variations [J]. Journal of Geophysical Research: Atmospheres (1984-2012), 2012, 117(D13), DOI:10. 1029/2012JD017577.
[20]
Kalnay E, Kanamitsu M, Kistler R, et al. The NCEP/NCAR 40-year reanalysis project [J]. Bulletin of the American Meteorological Society, 1996,77(3):437-471.
[21]
Levy R C, Remer L A, Kleidman R G, et al. Global evaluation of the Collection 5MODIS dark-target aerosol products over land [J]. Atmospheric Chemistry and Physics, 2010,10(21):10399-10420.
[22]
Torres O, Tanskanen A, Veihelmann B, et al. Aerosols and surface UV products from Ozone Monitoring Instrument observations: An overview [J]. Journal of Geophysical Research: Atmospheres (1984-2012), 2007,112(D24), DOI:10.1029/2007JD008809.
[23]
Ahn C, Torres O, Bhartia P K. Comparison of ozone monitoring instrument UV aerosol products with Aqua/Moderate Resolution Imaging Spectroradiometer and Multiangle Imaging Spectroradiometer observations in 2006 [J]. Journal of Geophysical Research: Atmospheres (1984-2012), 2008, 113(D16),DOI:10.1029/2007JD008832.
[24]
Liu Z, Liu D, Huang J, et al. Airborne dust distributions over the Tibetan Plateau and surrounding areas derived from the first year of CALIPSO lidar observations [J]. Atmospheric Chemistry and Physics, 2008,8(16):5045-5060.
[25]
Mielonen T, Arola A, Komppula M, et al. Comparison of CALIOP level 2aerosol subtypes to aerosol types derived from AERONET inversion data [J]. Geophysical Research Letters, 2009,36(18),DOI:10.1029/2009GL039609.
[26]
Omar A H, Winker D M, Vaughan M A, et al. The CALIPSO automated aerosol classification and lidar ratio selection algorithm [J]. Journal of Atmospheric and Oceanic Technology, 2009,26(10):1994-2014.
[27]
Draxler R R, Hess G D. Description of the HYSPLIT4modeling system [A]. 1997.
Nishanth T, Praseed K M, Satheesh Kumar M K, et al. Observational study of surface O3, NOx, CH4 and total NMHCs at Kannur, India [J]. Aerosol. Air. Qual. Res, 2014(14):1074-1088.
[34]
Han S, Bian H, Feng Y, et al. Analysis of the Relationship between O3, NO and NO2 in Tianjin, China [J]. Aerosol Air Qual. Res., 2011(11):128-139.
[35]
Lu Z, Streets D G, de Foy B, et al. Ozone Monitoring Instrument observations of interannual increases in SO2 emissions from Indian coal-fired power plants during 2005~2012 [J]. Environmental Science & Technology, 2013,47(24):13993-14000.
Xie Y Y, Zhao B, Zhang L, et al. Spatiotemporal variations of PM2.5 and PM10 concentrations between 31Chinese cities and their relationships with SO2, NO2, CO and O3 [J]. Particuology, 2015,20:141-149.
Althausen D, Engelmann R, Baars H, et al. Portable Raman lidar PollyXT for automated profiling of aerosol backscatter extinction and depolarization [J]. Journal of Atmospheric and Oceanic Technology, 2009,26(11):2366-2378.