High-altitude and long-range transport of aerosols causing regional severe haze during extreme dust storms explains why afforestation does not prevent storms

Guo, Ping; Shang, Yu; Wang, Liqiang; Li, Pengfei; Li, Zhen; Mehmood, Khalid; Xue, Chen; Liu, Weiping; Zhu, Yannian; Yu, Xin; Alapaty, Kiran; Lichtfouse, Éric; Rosenfeld, Daniel; Seinfeld, John H.

doi:10.1007/s10311-019-00858-0

Cited by 18 publications

(9 citation statements)

References 36 publications

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“…Relatively low (<0.4) PM 2.5 and PM 10 ratios characterized the majority of cities, especially in spring and summer, suggesting the predominance of PM 10 in the atmosphere. This is likely linked with wind erosion, that results in a high frequency of dust‐storms of various degrees of intensity (Guo et al ., 2019). The lowest PM 2.5 /PM 10 ratios were in Jiayuguan with values 0.24, 0.19 and 0.23 in April, May and June, respectively, and the highest ratios were in Baotou in January, February and March with values 0.63, 0.71 and 0.57 (Table 1).…”

Section: Resultsmentioning

confidence: 99%

“…Aerosol particles directly interact with solar and terrestrial radiation by means of scattering and absorption and may also indirectly affect the dynamics and microstructure of clouds (Ackerman et al ., 2000; Kim and Ramanathan, 2008; Tiwari et al ., 2019). In addition, aerosols can have a significant impact on air quality, atmospheric visibility and human health, thus affecting social and economic activity (Wan et al ., 2011; Hao and Liu, 2016; Guo et al ., 2019; Kaskaoutis et al ., 2019; Biswas et al, 2020; Filonchyk et al ., 2020a). Particulate matter (PM), including PM 2.5 (particles of aerodynamic diameter ≤2.5 μm) and PM 10 (≤10 μm), play an important role in this respect since high concentrations adversely affect human health (Yang et al ., 2012; Xing et al ., 2016).…”

Section: Introductionmentioning

confidence: 99%

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Air pollution in the Gobi Desert region: Analysis of dust‐storm events

Filonchyk

Peterson

Hurynovich

2021

Quart J Royal Meteoro Soc

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Air pollutants in nine cities of the Gobi Desert region are examined in this study. Mean concentrations of PM2.5 and PM10, retrieved from ground‐based air quality monitoring stations, were 36.2 ± 23.7 and 97.3 ± 84.5 μg·m−3, respectively. The highest concentrations of pollutants were in spring and winter. This can be explained by wind‐borne dust in the spring and emissions from domestic sources during the winter heating season. The highest PM2.5 and PM10 concentrations were registered in a period of dust‐storm activity with values of 343 μg·m−3 and 1,642 μg·m−3. Generally, clean continental (CC) was the dominant aerosol type (73.9%), followed by mixed (MX) aerosol type (20.4%) with insignificant contribution of clean marine (CM) (2.1%), urban/industrial and biomass burning (UI/BB) (0.9%) and desert dust (DD) (2.7%) aerosol types. The various measures of pollution retrieved from AERONET stations, including aerosol optical depth (AOD), Ångström exponent (AE), asymmetry parameter (AP), single scattering albedo (SSA) and aerosol volume size distribution (AVSD), specify the content of coarse aerosol fractions in the period of dust activity. The aerosol radiative forcing at the bottom of the atmosphere (ARFBOA) and the top of the atmosphere (ARFTOA) during dust days were estimated to be −115.76 and −241.31 W·m−2, with a corresponding heating rate of 3.52 K·day−1. According to the backward and forward trajectories of air masses, the dust cloud moved to the east and southeast from the epicentre, affecting the eastern and the central parts of the country. This study may advise environmental policy, as it showed how controlling causes of pollution can improve air quality.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Air pollution in the Gobi Desert region: Analysis of dust‐storm events

Filonchyk

Peterson

Hurynovich

2021

Quart J Royal Meteoro Soc

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“…No PM composition data are available to address the effect of composition on respiratory defense mechanism efficiency (e.g., Engelbrecht et al., 2009 ; Griffin, 2007 ). There is still the possibility that this result was due to varying sizes and composition within the particulate matter population related with the evolution of a pseudo-steady state boundary-layer aerosol population, and/or with the long range transport of ILI micro-organisms (e.g., Sajadi et al., 2020 ; Guo et al., 2019 ; Nakata et al., 2013 ; Roelofs, 2013 ; Salvador et al., 2013 ; VanCuren et al., 2012 ; Griffin, 2007 ; Tafuro et al., 2006 ; Perry et al., 1997 ; Pruppacher and Jaenicke, 1995 ; Hoppel et al., 1989 , 1990 ).…”

Section: Resultsmentioning

confidence: 99%

Relationship between temporal anomalies in PM2.5 concentrations and reported influenza/influenza-like illness activity

DeFelice

2020

Heliyon

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A small number of studies suggest atmospheric particulate matter with diameters 2.5 micron and smaller (PM 2.5 ) may possibly play a role in the transmission of influenza and influenza-like illness (ILI) symptoms. Those studies were predominantly conducted under moderately to highly polluted outdoor atmospheres. The purpose of this study was to extend the data set to include a less polluted atmospheric environment. A relationship between PM2.5 and ILI activity extended to include lightly to moderately polluted atmospheres could imply a more complicated mechanism than that suggested by existing studies. We obtained concurrent PM 2.5 mass concentration data, meteorological data and reported Influenza and influenza-like illness (ILI) activity for the light to moderately polluted atmospheres over the Tucson, AZ region. We found no relation between PM2.5 mass concentration and ILI activity. There was an expected relation between ILI, activity, temperature, and relative humidity. There was a possible relation between PM2.5 mass concentration anomalies and ILI activity. These results might be due to the small dataset size and to the technological limitations of the PM measurements. Further study is recommended since it would improve the understanding of ILI transmission and thereby improve ILI activity/outbreak forecasts and transmission model accuracies.

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“…Based on a flexible model and automatic differentiation, although the simulation of the vertical profile is not perfect, the proposed method achieved the state-of-the-art performance in the conversion and downstream application of PM 2.5 estimation. Third, all the discussed conversion methods work best in the areas dominated by regional aerosols residing in the boundary layer, but work less well in the areas dominated by long-range aerosol transport at higher altitudes [56,57].…”

Section: Discussionmentioning

confidence: 99%

Optimal Inversion of Conversion Parameters from Satellite AOD to Ground Aerosol Extinction Coefficient Using Automatic Differentiation

2020

Remote Sensing

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Satellite aerosol optical depth (AOD) plays an important role for high spatiotemporal-resolution estimation of fine particulate matter with diameters ≤2.5 μm (PM2.5). However, the MODIS sensors aboard the Terra and Aqua satellites mainly measure column (integrated) AOD using the aerosol (extinction) coefficient integrated over all altitudes in the atmosphere, and column AOD is less related to PM2.5 than low-level or ground-based aerosol (extinction) coefficient (GAC). With recent development of automatic differentiation (AD) that has been widely applied in deep learning, a method using AD to find optimal solution of conversion parameters from column AOD to the simulated GAC is presented. Based on the computational graph, AD has considerably improved the efficiency in applying gradient descent to find the optimal solution for complex problems involving multiple parameters and spatiotemporal factors. In a case study of the Jing-Jin-Ji region of China for the estimation of PM2.5 in 2015 using the Multiangle Implementation of Atmospheric Correction AOD, the optimal solution of the conversion parameters was obtained using AD and the loss function of mean square error. This solution fairly modestly improved the Pearson’s correlation between simulated GAC and PM2.5 up to 0.58 (test R2: 0.33), in comparison with three existing methods. In the downstream validation, the simulated GACs were used to reliably estimate PM2.5, considerably improving test R2 up to 0.90 and achieving consistent match for GAC and PM2.5 in their spatial distribution and seasonal variations. With the availability of the AD tool, the proposed method can be generalized to the inversion of other similar conversion parameters in remote sensing.

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High-altitude and long-range transport of aerosols causing regional severe haze during extreme dust storms explains why afforestation does not prevent storms

Cited by 18 publications

References 36 publications

Air pollution in the Gobi Desert region: Analysis of dust‐storm events

Air pollution in the Gobi Desert region: Analysis of dust‐storm events

Relationship between temporal anomalies in PM2.5 concentrations and reported influenza/influenza-like illness activity

Optimal Inversion of Conversion Parameters from Satellite AOD to Ground Aerosol Extinction Coefficient Using Automatic Differentiation

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