The better we understand two-way interactions between aerosols and meteorology and associated feedback, the more effectively we can mitigate air pollution and as well as mitigate climate forces and adapt to climate change¹. Heavy pollution of particular matters, such as PM_2.5, has been observed in China and other less-developed countries under the industrialization and urbanization in the past two decades. Although emission reduction efforts have significantly lowered particulate matter concentrations in China in recent years, the climatic effects of aerosols continue to be a major concern in the scientific communities². The secondary circulation (SC) in the atmospheric boundary layer (ABL) is well-known in the atmospheric science which plays a vital role in atmospheric motion as it not only relates to the dynamics of the basic circulation, it also serves as the driving force for maintaining and developing synoptic system and generating weather phenomena³. SC has been demonstrated to provide a primary pathway for exchange of air mass and atmospheric constituents between the ABL and the free atmosphere. SC can also suppress geostrophic winds, influence planetary boundary layer height, affect ABL energy balance, and disturb ABL turbulence⁴. But SC is less known in the air pollution research community.

What did we find?

We propose a two-way interaction dynamical mechanism between the secondary circulations (SCs) and PM concentrations. Suppose that the region is under the westerly wind regime, since heavy aerosol pollution tends to reduce in wind speed, the closer to the center of heavy pollution, the weaker the wind speed is. Consequently, the upstream area of heavy pollution region forms a convergence zone, and the downstream area becomes a divergence zone, which would generate vertical motions to maintain mass conservation. Under favorable synoptic-scale background meteorological conditions, the downward and upward airflow strengthen further, leading to the formation of a convergence zone above the divergence zone. Eventually, a strong and well-structured clockwise rotating SC and a weaker counterclockwise rotating SC are formed. But when the aerosol feedback impact is not very strong, often only the well-structured clockwise rotating SC appears.

The results show that in heavily PM_2.5 polluted Beijing-Tianjin-Hebei areas, the aerosol feedback is the primary factor on the occurrence and development of mesoscale SCs in the atmospheric boundary layer, although the synoptic background influences the location and characteristics of SCs. The largest variation in SC occurred during the afternoon, which should be related to the stronger solar radiation. We found that the reduction in wind speed caused by aerosol feedback and related convergence and divergence of the air mass play a pivotal role in SCs evolution. Modeling evidence reveal that the impact of aerosol feedback on SCs is proportional to PM_2.5 concentrations or precursor emissions. During the 2014 Asia-Pacific Economic Cooperation (APEC) with extraordinary emission reduction, the time levels of SCs significantly decreases to approximately 37.3% of the periods without emission reduction before and after APEC period. The simulated PM_2.5 during APEC are approximately 47.6% of before and after APEC period, and the measured concentration ratio at 47.7%.

Aerosol forces mesoscale secondary circulations occurrence and development in the atmospheric boundary layer, which have also been validated in the other two emission reduction events of 2015 and 2017, and also in January and July of 2014, 2017, and 2020 as the validation of long-term emission reduction policies. There is a strong relationship between the PM_2.5 levels and mesoscale SCs. During periods of high PM_2.5 concentrations, the time levels of SCs occurrence, the vorticity on vertical profile and the frequency of surface wind against the background of prevailing winds are stronger. We also found that the correlation coefficient between horizontal vorticity in the north-south direction and secondary PM_2.5 exceeds the correlation coefficient with total PM_2.5 during the APEC emission reduction event. The proportion of secondary PM_2.5 should be higher as winter approached, in winter, secondary aerosols may have a better correlation with SC. The relationship between simulated wind and SC is not better than observed, that should be because the input data for WRF are once every 6 hours, which cannot more accurately reflect the hourly variation of surface wind like the observed hourly data.

What do the study results mean?

 SCs are constrained by surface, meteorological, dynamic, and thermodynamic conditions within the ABL. The locations and sizes of SCs associated with aerosol concentration distribution under aerosol feedback, although different synoptic background wind fields could result in different characteristics of reinforced SCs. Since our proposed two-way interaction dynamical mechanism between the SCs and PM concentrations, is based on the universal phenomenon of aerosol reducing wind speed and constrained by the law of conservation of air mass, the relevant conclusions should also have some reference significance in other places. However, there are still uncertainties in the impact of aerosol feedback on weather or climate, such as aerosol-cloud interactions, the uncertainties in pollutant emission inventories⁵ and WRF input data which containing limited hourly meteorological variations. Additionally, the mechanism we proposed is the main process by which aerosols affect SCs, rather than the full chain of events associated with the feedback. Since the observed atmosphere is already polluted rather than clean air, the impact of anthropogenic aerosols on mesoscale SCs are likely to be more severe than the present research results. The emergence of SCs caused by aerosol feedback may disturb the weather system, especially under heavy pollution conditions, which may increase the uncertainty of weather simulation. There should be many aspects that need to be studied in the two-way interactions between aerosols and meteorology and associated feedback⁶, which could help promote our understanding of content and level of aerosol feedback to atmospheric changes.

 References

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