The impacts of the meteorology features on PM2.5 levels during a severe haze episode in central-east China

Abstract The most polluted urban agglomeration including 13 cities in Central-East China (112–122°E, 34–42°N) were selected to study the impacts of meteorology features on PM2.5 levels during the severe haze episode by using observational PM2.5 concentration, surface and balloon sounding meteorology data. The study results showed that the temporal changing of PM2.5 in the 13 cities showed well correlation at the haze beginning, maintenance, and ending period due to the similar 500 hPa circulation and surface sea level pressure pattern. The increasing of surface relative humidity (RH) and temperature preceded PM2.5 accumulation when haze began. RH usually reached up to 90–95% during the period of PM2.5 peak, suggesting the possible contribution of high humidity to extreme PM2.5 values. In contrast to the similar circulation of upper air and surface pressure pattern, the divergences of local PBL meteorology, especially their vertical structure, were very obvious, which was the major meteorology cause for the different PM2.5 levels in these cities. The temperature rise at 850 hPa layer was higher than that at 925 hPa, which was higher than that at 1000 hPa, leading to the formation of temperature inversion. This was the most important trigger factor for haze. PM2.5 maximum generally occurred within 12 h after the formation of the strongest inversion in each city. PM2.5 levels in the 13 cities strongly depend on their reverse intensity: for the cities where the inversion was strong and long lasting, its PM2.5 was often the highest. Stable inversions are more likely to form in the transitional area from the northwestern mountains to the southeastern plains because of the mountain's blocking of cold air and the warming of boundary layer by sinking airflow from the mountaintop. This is the major meteorology cause for the frequent occurrence of the extreme PM2.5 levels in middle-south plain of Hebei province. This study reminds us that local boundary layer and inversion conditions, closely related with geographical location and local topography, contributes greatly to local PM2.5 levels and should be fully considered in the emission reduction and industrial layout policy by government.

[1]  Xiao-Ming Hu,et al.  Evaluation of the updated YSU planetary boundary layer scheme within WRF for wind resource and air quality assessments , 2013 .

[2]  Yuan Cheng,et al.  Exploring the severe winter haze in Beijing: the impact of synoptic weather, regional transport and heterogeneous reactions , 2015 .

[3]  Lulu Zhang,et al.  Haze in China: current and future challenges. , 2014, Environmental pollution.

[4]  P. Zhao,et al.  Characteristics of concentrations and chemical compositions for PM 2.5 in the region of Beijing, Tianjin, and Hebei, China , 2013 .

[5]  Renjian Zhang,et al.  Variations in PM2.5, TSP, BC, and trace gases (NO2, SO2, and O3) between haze and non-haze episodes in winter over Xi'an, China , 2015 .

[6]  A. Mellouki,et al.  Severe haze episodes and seriously polluted fog water in Ji'nan, China. , 2014, The Science of the total environment.

[7]  X. Tie,et al.  Characteristics of heavy aerosol pollution during the 2012–2013 winter in Beijing, China , 2014 .

[8]  Tingting Liao,et al.  Process analysis of characteristics of the boundary layer during a heavy haze pollution episode in an inland megacity, China. , 2016, Journal of environmental sciences.

[9]  Huarong Zhao,et al.  Relative contributions of boundary-layer meteorological factors to the explosive growth of PM2.5 during the red-alert heavy pollution episodes in Beijing in December 2016 , 2017, Journal of Meteorological Research.

[10]  Junji Cao,et al.  A budget analysis of the formation of haze in Beijing , 2015 .

[11]  Zifa Wang,et al.  Modeling study of regional severe hazes over mid-eastern China in January 2013 and its implications on pollution prevention and control , 2013, Science China Earth Sciences.

[12]  Francesc Rocadenbosch,et al.  Sensitivity of boundary-layer variables to PBL schemes in the WRF model based on surface meteorological observations, lidar, and radiosondes during the HygrA-CD campaign , 2016 .

[13]  Hong Wang,et al.  A multisource observation study of the severe prolonged regional haze episode over eastern China in January 2013 , 2014 .

[14]  Ting Yang,et al.  Formation and evolution mechanism of regional haze: a case study in the megacity Beijing, China , 2012 .

[15]  B. N. Holben,et al.  Investigating the aerosol optical and radiative characteristics of heavy haze episodes in Beijing during January of 2013 , 2014 .

[16]  M. Xue,et al.  Impact of the vertical mixing induced by low-level jets on boundary layer ozone concentration , 2013 .

[17]  X. Tie,et al.  Analysis of the causes of heavy aerosol pollution in Beijing, China: A case study with the WRF-Chem model , 2015 .

[18]  Ting Yang,et al.  Investigation of the sources and evolution processes of severe haze pollution in Beijing in January 2013 , 2014 .

[19]  Jianping Guo,et al.  A study of the meteorological causes of a prolonged and severe haze episode in January 2013 over central-eastern China , 2014 .

[20]  Fuqing Zhang,et al.  Evaluation of Three Planetary Boundary Layer Schemes in the WRF Model , 2010 .

[21]  Shulan Wang,et al.  Spatial and temporal variation of particulate matter and gaseous pollutants in 26 cities in China. , 2014, Journal of environmental sciences.

[22]  Yu Qu,et al.  Formation mechanism of continuous extreme haze episodes in the megacity Beijing, China, in January 2013 , 2015 .

[23]  Dui Wu,et al.  Observational studies of the meteorological characteristics associated with poor air quality over the Pearl River Delta in China , 2013 .