Connecting geomorphology to dust emission through high-resolution mapping of global land cover and sediment supply

Parajuli, Sagar; Zender, Charles S.

doi:10.1016/j.aeolia.2017.06.002

Cited by 47 publications

(70 citation statements)

References 67 publications

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“…To develop our data further, we also compared our results to the sediment supply map (SSM) and land surface map (LSM) proposed by Parajuli and Zender (2017). As demonstrated by Parajuli and Zender (2017), some inherent errors exist in the LSM classification, which might introduce errors in the interpretation of erodibility for specific surface types. According to the LSM, a large proportion of sites were classified as stabilized sand deposits, bedrock and bedrock with sediment, which appeared to contradict our field observations ( Figure S4).…”

Section: Landform Type and Dust Emission Potentialmentioning

confidence: 99%

“…As demonstrated by Parajuli and Zender (2017), some inherent errors exist in the LSM classification, which might introduce errors in the interpretation of erodibility for specific surface types. As suggested by Parajuli and Zender (2017), land surfaces that have high SSM values are considered high-emitting surfaces. [Colour figure can be viewed at wileyonlinelibrary.com] (2003b) (Parajuli and Zender, 2017).…”

Section: Landform Type and Dust Emission Potentialmentioning

confidence: 99%

“…As suggested by Parajuli and Zender (2017), land surfaces that have high SSM values are considered high-emitting surfaces. In this context, incorporation of field measurements is a clear priority in order to reliably represent the relationship between landform type and dust emission potential when using dust source schemes such as those of Parajuli and Zender (2017) and Bullard et al (2011). For instance, sparse grasslands and coppice dunes were identified as high emitters by the PI-SWERL, but they were likely classified as low-emissive surfaces according to the SSM values (geometric means:~0.19).…”

Section: Landform Type and Dust Emission Potentialmentioning

confidence: 99%

“…Bullard et al, 2011;Lee et al, 2012;Baddock et al, 2016;von Holdt et al, 2019). A recent example has combined hydrological processes and geomorphic signatures to collectively represent the geomorphic controls on dust sources (Parajuli and Zender, 2017). A recent example has combined hydrological processes and geomorphic signatures to collectively represent the geomorphic controls on dust sources (Parajuli and Zender, 2017).…”

Section: Introductionmentioning

confidence: 99%

“…Given the increasingly important role of human impact on soil erodibility, several studies have used satellite-based dust indicators allied with land cover maps to attribute dust emission to natural or anthropogenic sources (Ginoux et al, 2012;Lee et al, 2012;Parajuli et al, 2014). Baddock et al, 2009;Brindley et al, 2012;Ashpole and Washington, 2013;Parajuli and Zender, 2017). While satellite remote sensing is instrumental in identifying the spatial distribution of dust sources, there remain some uncertainties and inaccuracies related to the dust detection algorithms, overpass time, cloud effects and image/signal interpretation (e.g.…”

Section: Introductionmentioning

confidence: 99%

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Quantifying the effect of geomorphology on aeolian dust emission potential in northern China

Cui

Wiggs

et al. 2019

Earth Surf Processes Landf

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Representation of dust sources remains a key challenge in quantifying the dust cycle and its environmental and climatic impacts. Direct measurements of dust fluxes from different landform types are useful in understanding the nature of dust emission and characterizing the dynamics of soil erodibility. In this study we used the PI‐SWERL® instrument over a seasonal cycle to quantify the potential for PM10 (particles with diameter ≤10 μm) emission from several typical landform types across the Tengger Desert and Mu Us Sandy Land, northern China. Our results indicate that sparse grasslands and coppice dunes showed relatively high emission potentials, with emitted fluxes ranging from 10−1 to 101 mg m−2 s−1. These values were up to five times those emitted from sand dunes, and one to two orders of magnitude greater than the emissions from dry lake beds, stone pavements and dense grasslands. Generally, PM10 emission fluxes were seen to peak in the spring months, with significant reductions in summer and autumn (by up to 95%), and in winter (by up to 98%). Variations in soil moisture were likely a primary controlling factor responsible for this seasonality in PM10 emission. Our data provide a relative quantification of differences in dust emission potential from several key landform types. Such data allow for the evaluation of current dust source schemes proposed by prior researchers. Moreover, our data will allow improvements in properly characterizing the erodibility of dust source regions and hence refine the parameterization of dust emission in climate models. © 2019 John Wiley & Sons, Ltd. © 2019 John Wiley & Sons, Ltd.

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Section: Landform Type and Dust Emission Potentialmentioning

confidence: 99%

Section: Landform Type and Dust Emission Potentialmentioning

confidence: 99%

Section: Landform Type and Dust Emission Potentialmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Quantifying the effect of geomorphology on aeolian dust emission potential in northern China

Cui

Wiggs

et al. 2019

Earth Surf Processes Landf

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Quantifying Anthropogenic Dust Emissions

Webb¹,

Pierre

2018

Earth's Future

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Anthropogenic land use and land cover change, including local environmental disturbances, moderate rates of wind‐driven soil erosion and dust emission. These human‐dust cycle interactions impact ecosystems and agricultural production, air quality, human health, biogeochemical cycles, and climate. While the impacts of land use activities and land management on aeolian processes can be profound, the interactions are often complex and assessments of anthropogenic dust loads at all scales remain highly uncertain. Here, we critically review the drivers of anthropogenic dust emission and current evaluation approaches. We then identify and describe opportunities to: (1) develop new conceptual frameworks and interdisciplinary approaches that draw on ecological state‐and‐transition models to improve the accuracy and relevance of assessments of anthropogenic dust emissions; (2) improve model fidelity and capacity for change detection to quantify anthropogenic impacts on aeolian processes; and (3) enhance field research and monitoring networks to support dust model applications to evaluate the impacts of disturbance processes on local to global‐scale wind erosion and dust emissions.

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Impact of the land-use/cover on the dust emission using meteorological data and satellite imagery

Jebali

Chahouki

2022

Int. J. Environ. Sci. Technol.

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Connecting geomorphology to dust emission through high-resolution mapping of global land cover and sediment supply

Cited by 47 publications

References 67 publications

Quantifying the effect of geomorphology on aeolian dust emission potential in northern China

Quantifying the effect of geomorphology on aeolian dust emission potential in northern China

Quantifying Anthropogenic Dust Emissions

Impact of the land-use/cover on the dust emission using meteorological data and satellite imagery

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