Numerical simulations of the effects of regional topography on haze pollution in Beijing

Zhang, Ziyin; Xu, Xiangde; Qiao, Lin; Gong, Daoyi; Kim, Seong‐Joong; Wang, Yinjun; Mao, Rui

doi:10.1038/s41598-018-23880-8

Cited by 49 publications

(22 citation statements)

References 56 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, an obvious underestimation is found in Beijing from 25 to 26 December when a maximum hourly concentration of 600 µg m -3 was observed. The negative bias is also simulated by previous studies (Chen et al, 2018;Zhang et al, 2018b), and the possible reasons for the underestimation are (1) the bias in simulated meteorological conditions (e.g., underestimated RH 2 and overestimated WS 10 );…”

Section: Pm 25 and Its Componentssupporting

confidence: 72%

Assessing the formation and evolution mechanisms of severe haze pollution in Beijing−Tianjin−Hebei region by using process analysis

Chen¹,

Zhu²,

Liu³

et al. 2019

Preprint

View full text Add to dashboard Cite

Abstract. Fine&#8211;particle pollution associated with haze threatens human health, especially in the North China Plain, where extremely high PM2.5 concentrations were frequently observed during winter. In this study, the WRF&#8211;Chem model coupled with an improved integrated process analysis scheme was used to investigate the formation and evolution mechanisms of a haze event happened over Beijing&#8211;Tianjin&#8211;Hebei (BTH) in December 2015, including examining the contributions of local emission and outside transport to the absolute PM2.5 concentration in BTH, and the contributions of each detailed physical or chemical process to the variations in the PM2.5 concentration. The influence mechanisms of aerosol radiative forcing (including aerosol direct and indirect effects) were also examined by using the process analysis. During the aerosol accumulation stage (December 20&#8211;22, Stage_1), the average near&#8211;surface PM2.5 concentration in BTH was 250.0&#8201;&#181;g&#8201;m&#8722;3, which was contributed by local emission of 42.3&#8201;% and outside transport of 36.6&#8201;%. During the aerosol dispersion stage (December 23&#8211;27, Stage_2), the average concentration of PM2.5 was 107.9&#8201;&#181;g&#8201;m&#8722;3. The contribution of local emission increased to 50.9&#8201;%, while the contribution of outside transport decreased to 24.3&#8201;%. The 24&#8211;h change (23:00LST minus 00:00LST) in the near&#8211;surface PM2.5 concentration was +50.4&#8201;&#181;g&#8201;m&#8722;3 during Stage_1 and &#8722;41.5&#8201;&#181;g&#8201;m&#8722;3 during Stage_2. Contributions of aerosol chemistry process and vertical mixing process to the 24&#8211;h change were +43.8 (+17.9) &#181;g&#8201;m&#8722;3 and &#8722;161.6 (&#8722;221.6) &#181;g&#8201;m&#8722;3 for Stage_1 (Stage_2), respectively. Small differences in contributions from other processes were found between Stage_1 and Stage_2, such as advection process, cloud chemistry process, and so on. Therefore, the PM2.5 increase over BTH during haze formation stage (Stage_1) was mainly attributed to strong production by aerosol chemistry process and weak removal by vertical mixing process. When aerosol radiative feedback was considered, the 24&#8211;h PM2.5 increase was enhanced by 9.6 &#181;g&#8201;m&#8722;3 during Stage_1, which could be mainly attributed to the contributions of vertical mixing process (+39.8&#8201;&#181;g&#8201;m&#8722;3), advection process (&#8722;38.6&#8201;&#181;g&#8201;m&#8722;3) and aerosol chemistry process (+5.1&#8201;&#181;g&#8201;m&#8722;3). The restrained vertical mixing could be the primary reason for the enhancement in near&#8211;surface PM2.5 increase when aerosol radiative forcing was considered.

show abstract

Section: Pm 25 and Its Componentssupporting

confidence: 72%

Assessing the formation and evolution mechanisms of severe haze pollution in Beijing−Tianjin−Hebei region by using process analysis

Chen¹,

Zhu²,

Liu³

et al. 2019

Preprint

View full text Add to dashboard Cite

show abstract

“…All major aerosol species are considered in the MOSAIC scheme, including sulfate (SO 2− 4 ), nitrate (NO − 3 ), ammonium (NH + 4 ), chloride (Cl), sodium (Na), BC, primary organic mass, liquid water, and other inorganic mass (Zaveri et al, 2008). The aerosol size distribution is divided into discrete size bins defined by their lower and upper dry particle diameters (Zhao et al, 2010). In the current CBMZ/MOSAIC scheme, the formation of SOA (secondary organic aerosol) is not included (Zhang et al, 2012;Gao et al, 2016).…”

Section: Model Configurationmentioning

confidence: 99%

Assessing the formation and evolution mechanisms of severe haze pollution in the Beijing–Tianjin–Hebei region using process analysis

et al. 2019

View full text Add to dashboard Cite

Abstract. Fine-particle pollution associated with haze threatens human health, especially in the North China Plain region, where extremely high PM2.5 concentrations are frequently observed during winter. In this study, the Weather Research and Forecasting with Chemistry (WRF-Chem) model coupled with an improved integrated process analysis scheme was used to investigate the formation and evolution mechanisms of a haze event over the Beijing–Tianjin–Hebei (BTH) region in December 2015; this included an examination of the contributions of local emissions and regional transport to the PM2.5 concentration in the BTH area, and the contributions of each detailed physical or chemical process to the variations in the PM2.5 concentration. The mechanisms influencing aerosol radiative forcing (including aerosol direct and indirect effects) were also examined by using process analysis. During the aerosol accumulation stage (16–22 December, Stage 1), the near-surface PM2.5 concentration in the BTH region increased from 24.2 to 289.8 µg m−3, with the contributions of regional transport increasing from 12 % to 40 %, while the contribution of local emissions decreased from 59 % to 38 %. During the aerosol dispersion stage (23–27 December, Stage 2), the average concentration of PM2.5 was 107.9 µg m−3, which was contributed by local emissions (51 %) and regional transport (24 %). The 24 h change (23:00 minus 00:00 LST) in the near-surface PM2.5 concentration was +43.9 µg m−3 during Stage 1 and −41.5 µg m−3 during Stage 2. The contributions of aerosol chemistry, advection, and vertical mixing to the 24 h change were +29.6 (+17.9) µg m−3, −71.8 (−103.6) µg m−3, and −177.3 (−221.6) µg m−3 during Stage 1 (Stage 2), respectively. Small differences in the contributions of other processes were found between Stage 1 and Stage 2. Therefore, the PM2.5 increase over the BTH region during the haze formation stage was mainly attributed to strong production by the aerosol chemistry process and weak removal by the advection and vertical mixing processes. When aerosol radiative feedback was considered, the 24 h PM2.5 increase was enhanced by 4.8 µg m−3 during Stage 1, which could be mainly attributed to the contributions of the vertical mixing process (+22.5 µg m−3), the advection process (−19.6 µg m−3), and the aerosol chemistry process (+1.2 µg m−3). The restrained vertical mixing was the primary reason for the enhancement in the near-surface PM2.5 increase when aerosol radiative forcing was considered.

show abstract

“…Second, meteorological conditions strongly influence haze pollution through the accumulation or diffusion, spread, and regional transport of air pollutants as well as the formation of secondary aerosols, which are generated by complicated physical and chemical reactions (Jeong & Park, ; Li et al, ; Marais et al, ; Ramsey et al, ; Wang et al, ; Yin & Wang, ; Zhang et al, ; Zheng et al, ). Third, topography influences haze pollution that occurs in Beijing and eastern China (Xu et al, ; Zhang et al, ).…”

Section: Introductionmentioning

confidence: 99%

Possible Influence of the Antarctic Oscillation on Haze Pollution in North China

et al. 2019

Self Cite

View full text Add to dashboard Cite

In this study, the possible influence of the Antarctic oscillation (AAO) on winter haze pollution (indicated by atmospheric visibility after rain, fog, dust, snowstorms, etc. are removed) in North China (NC) was investigated. The results show that the mean winter visibility (December‐January‐February visibility) throughout most of eastern China is negatively correlated with the preceding AAO (August‐September‐October (ASO)‐AAO), especially in NC. The interannual correlation coefficient between DJF‐VIS in NC and the ASO‐AAO is −0.52, which is significant at the 99% level. The negative correlation suggests that an enhancing (weakening) ASO‐AAO could be conducive to increases (decreases) of haze pollution in NC in boreal winter. The responses of local and regional meteorological conditions to the ASO‐AAO support the relationship between the ASO‐AAO and winter air pollution in NC. A preliminary mechanism analysis shows that a positive ASO‐AAO may induce a sea surface temperature warming tendency in the Northwestern Southern Indian Ocean. This warming then causes a wave train‐like pattern in the upper troposphere along the jet stream and an anomalous zonal cell that weakens the regional Hadley circulation from the Maritime continents to East Asia. All of these factors are favorable to the formation of anomalous southerly and haze pollution in NC.

show abstract

Numerical simulations of the effects of regional topography on haze pollution in Beijing

Cited by 49 publications

References 56 publications

Assessing the formation and evolution mechanisms of severe haze pollution in Beijing−Tianjin−Hebei region by using process analysis

Assessing the formation and evolution mechanisms of severe haze pollution in Beijing−Tianjin−Hebei region by using process analysis

Assessing the formation and evolution mechanisms of severe haze pollution in the Beijing–Tianjin–Hebei region using process analysis

Possible Influence of the Antarctic Oscillation on Haze Pollution in North China

Contact Info

Product

Resources

About