Geng Xinze, Liu Chang, Liu Xuyan, et al. Formation mechanism of heavy PM2.5 pollution in Harbin in January 2020. J Appl Meteor Sci, 2024, 35(6): 737-746. DOI:  10.11898/1001-7313.20240609.
Citation: Geng Xinze, Liu Chang, Liu Xuyan, et al. Formation mechanism of heavy PM2.5 pollution in Harbin in January 2020. J Appl Meteor Sci, 2024, 35(6): 737-746. DOI:  10.11898/1001-7313.20240609.

Formation Mechanism of Heavy PM2.5 Pollution in Harbin in January 2020

DOI: 10.11898/1001-7313.20240609
  • Received Date: 2024-05-10
  • Rev Recd Date: 2024-08-14
  • Publish Date: 2024-11-30
  • In the context of China's commitment to improve air quality enhancement, cities within severe cold climate zones, exemplified by Harbin continue to confront the exigent issue of fine particulate matter (PM2.5) pollution, notably during winter. Despite nationwide initiatives aimed at mitigating air pollution, Harbin's unique geographical and climatic conditions, combined with its predominant economic activities, have led to consistently high levels of PM2.5 during winter. An episode of severe PM2.5 pollution is observed in January 2020, with the monthly average mass concentration of PM2.5 peaking at 155.0 μg·m-3, significantly surpassing national standards. To explore the mechanism of this severe PM2.5 pollution episode, an integrated analysis of chemical compositions and influencing factors is conducted during this period. In the meantime, methods of backward trajectory clustering and the weighted potential source contribution function (WPSCF) are employed to investigate source areas and transport pathways of air pollutants. Results indicate that the severe PM2.5 pollution in Harbin mainly originates from primary emissions, with biomass burning contributing significantly. During the observation period, the concentration of levoglucosan in PM2.5, a common tracer of biomass burning, reaches as high as 1.1 μg·m-3, which is 3.7 to 5.5 times higher than that in other regions experiencing severe biomass burning pollution during winter. Furthermore, research findings indicate that meteorological conditions play a significant role in exacerbating PM2.5 pollution in Harbin. High relative humidity (averaging at 80.0%) combined with extremely low temperatures (averaging at -18.0 ℃) provided favorable conditions for secondary aerosol formation. Under such low-temperature and high-humidity conditions, the average sulfur oxidation rate reaches as high as 25.6%, and the nitrogen oxidation rate reaches 10.8%. It significantly increases the contribution of secondary aerosols to PM2.5 in Harbin. Additionally, this study also reveals the impact of regional transportation on the air quality of Harbin. It indicates that the air quality of Harbin is influenced not only by local emissions but also by the transportation of pollutants from neighboring cities such as Suihua, Daqing, Changchun, and Songyuan. The inter-city transfer of pollution highlights the close connection of air pollution issues within the region. Through the comprehensive analysis of causes of a severe PM2.5 pollution event in Harbin during winter from multiple perspectives, a scientific basis is provided for understanding causes for air pollution in similar cold climate.
  • Fig. 1  Daily variations of reconstructed PM2.5 concentration and meteorological factors of Harbin in Jan 2020

    Fig. 2  Proportions of secondary inorganic ions in reconstructed PM2.5 concentrations of Harbin in Jan 2020

    Fig. 3  Daily variation of SOR and NOR of Harbin in Jan 2020

    (data missing on 21 Jan)

    Fig. 4  Daily variations of OC, EC concentrations with their ratio in PM2.5 of Harbin in Jan 2020

    Fig. 5  Relationship of LG concentration to concentrations of reconstructed PM2.5(a) and OC(b) of Harbin in Jan 2020

    Fig. 6  Backward airmass trajectory clusters of Harbin in Jan 2020

    (clustered from 742 paths of 24 h backward trajectories with height of 100 m)

    Fig. 7  Potential source areas of PM2.5 with its main chemical components of Harbin in Jan 2020

    Table  1  Five types of airmass trajectories affecting Harbin in Jan 2020

    聚类 轨迹数量 轨迹数量占比/% 平均质量浓度/(μg·m-3)
    1 121 17.0 211.3
    2 175 24.6 190.8
    3 292 41.1 157.8
    4 103 14.5 99.0
    5 20 2.8 16.5
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  • [1]
    Pant P, Guttikunda S K, Peltier R E. Exposure to particulate matter in India: A synthesis of findings and future directions. Environ Res, 2016, 147: 480-496. doi:  10.1016/j.envres.2016.03.011
    [2]
    Huang X, Ding A J, Wang Z L, et al. Amplified transboundary transport of haze by aerosol-boundary layer interaction in China. Nat Geosci, 2020, 13: 428-434. doi:  10.1038/s41561-020-0583-4
    [3]
    Xu X B. Observational study advances of haze and photochemical pollution in China. J Appl Meteor Sci, 2016, 27(5): 604-619. doi:  10.11898/1001-7313.20160509
    [4]
    Health Effects Institute. State of Global Air 2020. Special Report. Boston: Health Effects Institute, 2020.
    [5]
    Zhang Q, Zheng Y X, Tong D, et al. Drivers of improved PM2.5 air quality in China from 2013 to 2017. PNAS, 2019, 116(49): 24463-24469. doi:  10.1073/pnas.1907956116
    [6]
    Chen W W, Liu Y, Wu X W, et al. Spatial and temporal characteristics of air quality and cause analysis of heavy pollution in Northeast China. Environ Sci, 2019, 40(11): 4810-4823.
    [7]
    Wang P, Liu D C, Mukherjee A, et al. Air pollution governance in China and India: Comparison and implications. Environ Sci Policy, 2023, 142: 112-120. doi:  10.1016/j.envsci.2023.02.006
    [8]
    Xi L Z, Ba L, Pang Z Y, et al. Aerosol characteristics of dust weather on north slope of the Qilian Mountains. J Appl Meteor Sci, 2024, 35(3): 311-322. doi:  10.11898/1001-7313.20240305
    [9]
    Wu X T, Wang X Y, Zheng D, et al. Effects of different aerosols on cloud-to-ground lightning activity in the Yangtze River Delta. J Appl Meteor Sci, 2023, 34(5): 608-618. doi:  10.11898/1001-7313.20230509
    [10]
    Feng Y Y, Ning M, Lei Y, et al. Defending blue sky in China: Effectiveness of the "Air Pollution Prevention and Control Action Plan" on air quality improvements from 2013 to 2017. J Environ Manag, 2019, 252. DOI:  10.1016/j.jenvman.2019.109603.
    [11]
    Zhou B X, Zhu L F, Wu H, et al. Accuracy of atmospheric profiles retrieved from microwave radiometer and its application to precipitation forecast. J Appl Meteor Sci, 2023, 34(6): 717-728. doi:  10.11898/1001-7313.20230607
    [12]
    Chyi D, He L F. Stage characteristics and mechanisms of extreme high temperature in China in summer of 2022. J Appl Meteor Sci, 2023, 34(4): 385-399. doi:  10.11898/1001-7313.20230401
    [13]
    Wang M M, Ding M H, Lü J M, et al. Climatology of winter cold waves and associated atmospheric circulation anomalies in China during the last 40 years. J Appl Meteor Sci, 2024, 35(3): 298-310. doi:  10.11898/1001-7313.20240304
    [14]
    Cheng Y, Yu Q Q, Liu J M, et al. Strong biomass burning contribution to ambient aerosol during heating season in a megacity in Northeast China: Effectiveness of agricultural fire bans?. Sci Total Environ, 2021, 754. DOI:  10.1016/j.scitotenv.2020.142144.
    [15]
    Zhang M M, Zhao C Y, Fang Y H, et al. Assessment and prediction of climate change in Northeast China based on new climate state background. J Meteor Environ, 2023, 39(4): 95-102.
    [16]
    Fu D L, Shi X F, Xing Y F, et al. Contributions of extremely unfavorable meteorology and coal-heating boiler control to air quality in December 2019 over Harbin, China. Atmos Pollut Res, 2021, 12(11). DOI:  10.1016/j.apr.2021.101217.
    [17]
    Li W, Zhao H J, Wang C S, et al. Variation characteristics of aerosol optical depth in Northeast China from 2003 to 2022. J Appl Meteor Sci, 2024, 35(2): 211-224. doi:  10.11898/1001-7313.20240207
    [18]
    Li B, Shi X F, Liu Y P, et al. Long-term characteristics of criteria air pollutants in megacities of Harbin-Changchun megalopolis, Northeast China: Spatiotemporal variations, source analysis, and meteorological effects. Environ Pollut, 2020, 267. DOI:  10.1016/j.envpol.2020.115441.
    [19]
    Ke H B, Gong S L, He J J, et al. Assessment of open biomass burning impacts on surface PM2.5 concentration. J Appl Meteor Sci, 2020, 31(1): 105-116. doi:  10.11898/1001-7313.20200110
    [20]
    Ma Y J, Zhao H J, Liu Y F, et al. Analysis of aerosol concentration variation and weather characteristics of heavy pollution events in Northeast China. J Meteor Environ, 2021, 37(5): 13-19.
    [21]
    Liang L L, Sun J Y, Zhang Y M, et al. Comparison of chemical components characteristics of PM2.5 between haze and clean periods during summertime in Lin'an. Environ Sci, 2018, 39(7): 3042-3050.
    [22]
    Cheng Y, Cao X B, Yu Q Q, et al. Synergy of multiple drivers leading to severe winter haze pollution in a megacity in Northeast China. Atmos Res, 2022, 270. DOI:  10.1016/j.atmosres.2022.106075.
    [23]
    Sun X Z, Wang K, Li B, et al. Exploring the cause of PM2.5 pollution episodes in a cold metropolis in China. J Clean Prod, 2020, 256. DOI:  10.1016/j.jclepro.2020.120275.
    [24]
    Yan P, Huan N, Zhang Y M, et al. Size resolved aerosol OC, EC at a regional background station in the suburb of Beijing. J Appl Meteor Sci, 2012, 23(3): 285-293. http://qikan.camscma.cn/article/id/20120304
    [25]
    Guo A H, Wang C Z, Deng H H, et al. Atmospheric dynamics analysis and simulation of the migration of fall armyworm. J Appl Meteor Sci, 2022, 33(5): 541-554. doi:  10.11898/1001-7313.20220503
    [26]
    Ma G, Huang J, Gong X Y, et al. Review of pre-processing techniques for meteorological satellite data assimilation in numerical prediction. J Appl Meteor Sci, 2024, 35(2): 142-155. doi:  10.11898/1001-7313.20240202
    [27]
    Wang R, Ding J L, Ma W, et al. Analysis of atmospheric particulates source in Urumqi based on PSCF and CWT models. Acta Sci Circumstantiae, 2021, 41(8): 3033-3042.
    [28]
    Wang Y Q, Zhang X Y, Draxler R R. TrajStat: GIS-based software that uses various trajectory statistical analysis methods to identify potential sources from long-term air pollution measurement data. Environ Model Softw, 2009, 24(8): 938-939.
    [29]
    Polissar A V, Hopke P K, Harris J M. Source regions for atmospheric aerosol measured at Barrow, Alaska. Environ Sci Technol, 2001, 35(21): 4214-4226.
    [30]
    Pan W, Zuo Z Y, Xiao D, et al. Interdecadal variation of haze days over China with atmospheric causes in recent 50 years. J Appl Meteor Sci, 2017, 28(3): 257-269. doi:  10.11898/1001-7313.20170301
    [31]
    Li R J, Huang M Y, Ding D P, et al. Warm cloud size distribution experiment based on 70 m3 expansion cloud chamber. J Appl Meteor Sci, 2023, 34(5): 540-551. doi:  10.11898/1001-7313.20230503
    [32]
    Zheng B, Zhang Q, Zhang Y, et al. Heterogeneous chemistry: A mechanism missing in current models to explain secondary inorganic aerosol formation during the January 2013 haze episode in North China. Atmos Chem Phys, 2015, 15(4): 2031-2049.
    [33]
    Wang G H, Zhang R Y, Gomez M E, et al. Persistent sulfate formation from London Fog to Chinese haze. PNAS, 2016, 113(48): 13630-13635.
    [34]
    Zhou B T, Shen H Z, Huang Y, et al. Daily variations of size-segregated ambient particulate matter in Beijing. Environ Pollut, 2015, 197: 36-42.
    [35]
    Zhong J T, Zhang X Y, Wang Y Q, 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. J Meteor Res, 2017, 31(5): 809-819.
    [36]
    Wang Y, Zhuang G S, Sun Y L, et al. The variation of characteristics and formation mechanisms of aerosols in dust, haze, and clear days in Beijing. Atmos Environ, 2006, 40(34): 6579-6591.
    [37]
    Li W G, Duan F K, Zhao Q, et al. Investigating the effect of sources and meteorological conditions on wintertime haze formation in Northeast China: A case study in Harbin. Sci Total Environ, 2021, 801. DOI:  10.1016/j.scitotenv.2021.149631.
    [38]
    Lim H J, Turpin B J. Origins of primary and secondary organic aerosol in Atlanta: Results of time-resolved measurements during the Atlanta Supersite Experiment. Environ Sci Technol, 2002, 36(21): 4489-4496.
    [39]
    Yang G Y, Zhao H M, Tong D Q, et al. Impacts of post-harvest open biomass burning and burning ban policy on severe haze in the northeastern China. Sci Total Environ, 2020, 716. DOI:  10.1016/j.scitotenv.2020.136517.
    [40]
    Yin S, Wang X F, Zhang X R, et al. Exploring the effects of crop residue burning on local haze pollution in Northeast China using ground and satellite data. Atmos Environ, 2019, 199: 189-201.
    [41]
    Zhao M Y, Cheng R X, Zhang C Y, et al. Photochemistry of levoglucosan in atmospheric aerosols: A review. Environ Chem, 2022, 41(6): 2044-2051.
    [42]
    Liang L L, Engling G, Cheng Y, et al. Biomass burning impacts on ambient aerosol at a background site in East China: Insights from a yearlong study. Atmos Res, 2020, 231. DOI:  10.1016/j.atmosres.2019.104660.
    [43]
    Liang L L, Du Z Y, Engling G, et al. Improved biomass burning pollution in Beijing from 2011 to 2018. Atmos Environ, 2023, 310. DOI: 10.1016/j.atmosenv.2023.119969.
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    • Received : 2024-05-10
    • Accepted : 2024-08-14
    • Published : 2024-11-30

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