Severe winter haze days in the Beijing–Tianjin–Hebei region from 1985 to 2017 and the roles of anthropogenic emissions and meteorology

Abstract

Abstract. We applied a global 3-D chemical transport model (GEOS-Chem) to examine the variations in the frequency and intensity in severe winter haze days (SWHDs) in Beijing–Tianjin–Hebei (BTH) from 1985 to 2017 and quantified the roles of changes in anthropogenic emissions and/or meteorological parameters. Observed SWHDs were defined as the days with daily mean PM2.5 concentration exceeding 150 µg m−3, and simulated SWHDs were identified by using the same threshold but with adjustment on the basis of simulation biases. Comparisons between the simulated SWHDs and those obtained from the observed PM2.5 concentrations and atmospheric visibility showed that the model can capture the spatial and temporal variations in SWHDs in China; the correlation coefficient between the simulated and observed SWHDs is 0.98 at 161 grids in China. From 1985 to 2017, with changes in both anthropogenic emissions and meteorological parameters, the simulated frequency (total severe haze days in winter) and intensity (PM2.5 concentration averaged over severe haze days in winter) of SWHDs in BTH showed increasing trends of 4.5 d per decade and 13.5 µg m−3 per decade, respectively. The simulated frequency exhibited fluctuations from 1985 to 2017, with a sudden decrease from 1992 to 2001 (29 to 10 d) and a rapid growth from 2003 to 2012 (16 to 47 d). The sensitivity simulations indicated that variations in meteorological parameters played a dominant role during 1992–2001, while variations in both emissions and meteorological parameters were important for the simulated frequency trend during 2003–2012 (simulated trends were 27.3 and 12.5 d per decade owing to changes in emissions alone and changes in meteorology alone, respectively). The simulated intensity showed a steady increase from 1985 to 2017, which was driven by changes in both emissions and meteorology. Process analysis on all SWHDs during 1985–2017 indicated that transport was the most important process for the formation of SWHDs in BTH with a relative contribution of 65.3 %, followed by chemistry (17.6 %), cloud processes (−7.5 %), dry deposition (−6.4 %), and planetary boundary layer (PBL) mixing (3.2 %). Further examination showed that SWHDs exhibited large interannual variations in frequency and intensity, which were mainly driven by changes in meteorology. The results of this study have important implications for the control of SWHDs in BTH.

Roles of climate variability on the rapid increases of early winter haze pollution in North China after 2010

“…Excluding the year 2010 did not affect the change in the trend of the two periods, with a decreased rate of 3.82 d per decade during the 1991-2009 period and an increased rate of 20.76 d per decade during the 2011-2018 period (passing the 95 % t test). In addition, Dang and Liao (2019) confirmed the varying trend of HD NC via simulations of the global 3-D chemical transport (GEOS-Chem) model; using the well-simulated frequency of serious haze days in winter, they also revealed the abovementioned changing trend of HD NC , i.e., decreasing in the early period and increasing in the later period. To further determine the reliability of the post-2010 upward trend of HD NC , we used hourly PM 2.5 concentrations observed at the US embassy in Beijing from 2009 to 2017 and the PM 2.5 concentrations over North China monitored by China National Environmental Monitoring Centre from 2014 to 2018 to count the number of days when the PM 2.5 concentrations were >75 and >100 µg m −3 (Fig.…”

“…The GEOS-Chem model has been widely used. Dang and Liao (2019) used the model to show that the simulated spatial patterns and daily variations of winter PM 2.5 based on GEOS-Chem agree well with the observations from 2013 to 2017, which are the available years with measured PM 2.5 . We selected the year of 2015, as emission reduction just begun to strengthen, and 2017, as this is when the air pollution prevention and management plan for "2 + 26" cities launched (Yin and Zhang, 2020), as two representative years to simulate the actual PM 2.5 concentrations, so as to evaluate the performance of the GEOS-Chem model.…”

“…2), and HD NC displayed this feature as well. The GEOS-Chem simulations with changing emissions and fixed meteorological conditions failed to reproduce the change trend of haze (Dang and Liao, 2019); however, with varying meteorology and fixed emissions, they could recognize the interannual variation in haze days. We designed an experiment driven by changing meteorological conditions in winter from 1980 to 2018 and fixed emissions at the relatively high 2010 level.…”

Emergency Response Measures to Alleviate a Severe Haze Pollution Event in Northern China during December 2015: Assessment of Effectiveness

“…The annual mean PM 2.5 concentrations in Beijing and in BTH in 2017 were reduced to 58 µg m -3 and 64 µg m -3 (Ministry of Ecology and Environment of the People's Republic of China, 2018), respectively, both meeting the improvement targets set by the Action Plan. However, analyses of observations showed that the frequency and intensity of wintertime haze events over the NCP have not shown significant decline since 2013 Dang and Liao, 2019).…”

“…The region of the North China Plain (hereafter referred to as the "NCP", as shown in Fig. 1(b)), including the Beijing-Tianjin-Hebei (BTH) area and the surrounding provinces of Shandong and Henan, has been experiencing severe winter haze pollution events of hourly PM 2.5 concentrations exceeding 150 µg m -3 in recent years (Dang and Liao, 2019), which pose threats to public health (e.g., Chen et al, 2013). These severe wintertime PM 2.5 pollution events are typically associated with the accumulation of PM 2.5 and its precursors under stagnant weather conditions.…”