Understanding severe winter haze events in the North China Plain in 2014: roles of climate anomalies

Abstract

Abstract. Atmospheric pollution has become a serious environmental and social problem in China. Over the past 30 years, the number of winter (December–February) haze days over the North China Plain (WHDNCP) was greatest in 2014. In addition to anthropogenic influence, climate anomalies also played a role. Thus, it is necessary to analyze the anomalous atmosphere circulations associated with haze pollution of this year in detail. Near the surface, the weaker East Asian winter monsoon pattern, causing southerly winds over the North China Plain, could aggravate the situation of haze. In the lower and middle troposphere, taking the anticyclone circulation over North China as an intermediate system, the positive phases of the eastern Atlantic/western Russia (EA/WR), the western Pacific (WP), and the Eurasia (EU) patterns led to a worse air pollution dispersion condition that contributed to a larger number of WHDNCP. In 2014, these three patterns could be recognized from the wind anomalies in the lower troposphere. The preceding autumn (September–November) Arctic sea ice (ASI) anomalies over the eastern Hemisphere and the warmer winter surface over Eurasia might have induced or intensified the positive EA/WR pattern in 2014. These two external forcings, together with the pre-autumn sea surface temperature anomalies in the Pacific, might have also stimulated or enhanced the positive EU-like patterns. The anomalous surface temperature in autumn 2014 was efficient in intensifying anomalous circulations such as the positive phase of the WP pattern. The opposite case of minimum WHDNCP in 2010 further supports the mechanism of how EA/WR and WP patterns and associated external factors altered the local climate conditions to impact the WHDNCP.

Role of atmospheric circulations in haze pollution in December 2016

“…The temperature profile was collected with a sounding balloon twice per day. The calculation procedure for the haze data was consistent with that of Yin et al (2017), which was mainly based on Table 1. Correlation coefficients between the DHD NH and key indices from 1979 to 2016 and the ranks of key indices in 2016.…”

“…Therefore, anomalous atmospheric circulations play a key role in the formation of heavy haze pollution in winter (December-February; Chen and Wang, 2015). From the hemispheric and regional perspective, the positive phase of the Arctic Oscillation (Yin et al, 2015b), the weak East Asia winter monsoon (Li et al, 2015;Yin et al, 2015b), and the positive phase of the East Atlantic-West Russia (EA/WR) teleconnection (Yin et al, 2017) contribute to the occurrence of winter haze by modulating local anti-cyclone anomalies over North China. As a key local circulation, this anomalous anti-cyclone resulted in descending motion that contributed to a reduction in the height of the planetary boundary layer (PBL).…”

Fine particle pH for Beijing winter haze as inferred from different thermodynamic equilibrium models

“…Synoptic weather patterns are dominated by the Siberian high-pressure system (Jia et al, 2015), under which the northerly winds bring dry and clean air into this region with ambient RH often dropping to as low as about 20% (when aerosol particles are most likely solid). When the northerly winds slacken, often occurring during 25 the NCP winter haze events, the atmospheric conditions are characterized by stagnant inversion, weak southerly winds, and rapid accumulation of both air pollutants and water vapor, and the ambient RH often reaches 80-90% (when aerosol particles are most likely liquid) (Zheng et al, 2015;Tie et al, 2017;Sun et al, 2016;Gao et al, 2016;Yin et al, 2017). Recent field measurements of PM1 in winter Beijing by Liu et al (2017b) suggested that the phase state of particles was sensitive to ambient RH and that there existed a gradual transition from semisolid at RH of about 20% to liquid at RH of 30 about 60%.…”

“…Due to lack of detailed measurements of these species, a thorough evaluation of their effect is difficult. Here, we conduct a sensitivity test using the E-AIM model including oxalate (C2O4 2− ), which is the most abundant organic acid salt in PM2.5 in winter Beijing (Huang et al, 2005;Wang et al, 2017) and is also one of the 25 strongest organic acids (acid dissociation constants pKa1 = 1.27 and pKa2 = 4.27). Strong positive correlations are measured between oxalate and sulfate and their ratios are about 1-2% (Wang et al, 2017).…”

“…Here, we conduct a sensitivity test using the E-AIM model including oxalate (C2O4 2− ), which is the most abundant organic acid salt in PM2.5 in winter Beijing (Huang et al, 2005;Wang et al, 2017) and is also one of the 25 strongest organic acids (acid dissociation constants pKa1 = 1.27 and pKa2 = 4.27). Strong positive correlations are measured between oxalate and sulfate and their ratios are about 1-2% (Wang et al, 2017). Considering also the relative concentration levels of oxalate and other organic acid salts (Table S8), the oxalate concentration is set at 20% of sulfate in this test, which may represent the upper limit for the concentration of total organic acids.…”