Identifying the dominant local factors of 2000–2019 changes in dust loading over East Asia

Yao, Wenrui; Gui, Ke; Wang, Yaqiang; Che, Huizheng; Zhang, Xiaoye

doi:10.1016/j.scitotenv.2021.146064

Cited by 34 publications

(24 citation statements)

References 45 publications

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“…Against the backdrop of the continued absence of strong SDS events in NC in almost a decade (An et al, 2018;Liu et al, 2020;Yao et al, 2021), this unexpected resurgence of two mega SDS events has raised potential concern as to whether such extreme SDS events will occur frequently in the future or whether a fresh active cycle of dust will begin.…”

Section: Discussionmentioning

confidence: 99%

“…Next, however, the internal drivers are explored by focusing on the extent of local meteorological anomalies affecting the surface conditions in the dust source region. Previous studies have revealed that the variability of dust emission intensity in the dust source area of NC is mainly controlled by several local meteorological factors, such as temperature, PPT and VSW (Kim and Choi, 2015;Wu et al, 2018;Yao et al, 2021). These factors have previously been demonstrated to constrain the intensity of dust emissions and their variability on multiple timescales.…”

Section: Anomalous Meteorological Drivers Conducive To Dust Emissionsmentioning

confidence: 99%

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Two mega sand and dust storm events over northern China in March 2021: transport processes, historical ranking and meteorological drivers

Gui

Yao

Che

et al. 2021

Preprint

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Abstract. Although a remarkable reduction in the frequency of sand and dust storms (SDSs) in the past several decades has been reported over northern China (NC), two unexpected mega SDSs occurred on March 15–20, 2021 and March 27–29, 2021 (abbreviated as the “3.15” and “3.27” SDS events), which has reawakened widespread concern. This study characterizes the origins, transport processes, magnitudes of impact, and meteorological causes of these two SDS events using a long-term (2000–2021) dust optical depth (DOD) dataset retrieved from MODIS measurements and a comprehensive set of multiple satellite and ground-based observations combined with atmospheric reanalysis data. During the 3.15/3.27 event, the invasion of dust plumes greatly degraded the air quality over large areas of NC, reaching extremely hazardous levels, with the maximum daily mean PM10 concentration of 7058 µg m−3 (2670 µg m−3) recorded on March 15 (28). CALIOP observations show that during the 3.15 event the dust plume was lifted to an altitude of 4–8 km, and its range of impact extended from the dust source to the eastern coast of China. In contrast, the lifting height of the dust plume during the 3.27 event was lower than that during 3.15 event, which was also confirmed by ground-based Lidar observations. The MODIS-retrieved DOD data registered these two massive SDS events as the most intense episode in the same period in history over the past two decades. These two extreme SDS events were associated with both atmospheric circulation extremes and local meteorological anomalies that favored enhanced dust emissions in the Gobi Desert (GD) across southern Mongolia and NC. Meteorological analysis revealed that both SDS events were triggered by an exceptionally strong Mongolian cyclone generated at nearly the same location (along the central and eastern plateau of Inner Mongolia) in conjunction with a surface-level cold high-pressure system at the rear, albeit with differences in magnitude and spatial extent of impact. In the GD, the early melting of spring snow caused by near-surface temperature anomalies over dust source regions, together with negative soil moisture anomalies induced by decreased precipitation, formed drier and barer soil surfaces, which allowed for increased emissions of dust into the atmosphere by strongly enhanced surface winds generated by the Mongolian cyclone.

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Section: Discussionmentioning

confidence: 99%

Section: Anomalous Meteorological Drivers Conducive To Dust Emissionsmentioning

confidence: 99%

Two mega sand and dust storm events over northern China in March 2021: transport processes, historical ranking and meteorological drivers

Gui

Yao

Che

et al. 2021

Preprint

Self Cite

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“…Most previous studies focused on the relationship between large‐scale surface features and dusty weather (Kurosaki & Mikami, 2007; Y. Liu et al., 2020; H. Q. Song et al., 2016; Yao et al., 2021). However, the influence of different surface characteristics on dusty weather at local scales important too.…”

Section: Introductionmentioning

confidence: 99%

“…Q. Song et al, 2016;Yao et al, 2021). However, the influence of different surface characteristics on dusty weather at local scales important too.…”

mentioning

confidence: 99%

Impacts of Underlying Surface on the Dusty Weather in Central Inner Mongolian Steppe, China

Bao

Yong

et al. 2021

Earth and Space Science

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“…Aerosols, originating from anthropogenic and natural sources, have significant effects on the radiative budget of the earth-atmospheric system, climate change, atmospheric environment, and human health, especially in densely populated regions with frequent anthropogenic activities and heavy aerosol emissions (e.g., East Asia, South Asia, and Southeast Asia) [1][2][3][4][5]. However, examining the effects of aerosols effect through their properties poses great challenges because they exhibit short atmospheric lifetimes and strong spatiotemporal heterogeneity.…”

Section: Introductionmentioning

confidence: 99%

Long-Term Variation Assessment of Aerosol Load and Dominant Types over Asia for Air Quality Studies Using Multi-Sources Aerosol Datasets

Huang

Sun

et al. 2021

Remote Sensing

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Long-term (2000–2019) assessment of aerosol loads and dominant aerosol types at spatiotemporal scales using multi-source datasets can provide a strong impetus to the investigation of aerosol loads and to the targeted prevention control of atmospheric pollution in densely populated regions with frequent anthropogenic activities and heavy aerosol emissions. This study uses multi-source aerosol datasets, including Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA-2), Moderate Resolution Imaging Spectroradiometer (MODIS), and Aerosol Robotic Network (AERONET), to conduct a long-term variation assessment of aerosol load, high aerosol load frequency, and dominant aerosol types over Asia. The results indicate that regional aerosol type information with adequate spatial resolution can be combined with aerosol optical depth (AOD) values and heavy aerosol load frequency characterization results to explore the key contributors to air pollution. During the study period, the aerosol load over the North China Plain, Central China, Yangtze River Delta, Red River Delta, Sichuan Basin, and Pearl River Delta exhibited an increasing trend from 2000–2009 due to a sharp rise in aerosol emissions with economic development and a declining trend from 2010–2019 under stricter energy conservation controls and emissions reductions. The growth of urban/industrial (UI) type and biomass burning (BB) type aerosol emissions hindered the improvement of the atmospheric environment. Therefore, in future pollution mitigation efforts, focus should be on the control of UI-type and BB-type aerosol emissions. The Indus–Ganges River Plain, Deccan Plateau, and Eastern Ghats show a continuously increasing trend; however, the aerosol load growth rate of the last decade was lower than that of the first decade, which was mainly due to the decrease in the proportion of the mixed type aerosols.

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Identifying the dominant local factors of 2000–2019 changes in dust loading over East Asia

Cited by 34 publications

References 45 publications

Two mega sand and dust storm events over northern China in March 2021: transport processes, historical ranking and meteorological drivers

Two mega sand and dust storm events over northern China in March 2021: transport processes, historical ranking and meteorological drivers

Impacts of Underlying Surface on the Dusty Weather in Central Inner Mongolian Steppe, China

Long-Term Variation Assessment of Aerosol Load and Dominant Types over Asia for Air Quality Studies Using Multi-Sources Aerosol Datasets

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