Modelling of sand/dust emission in Northern China from 2001 to 2014

Du, Heqiang; Wang, Tao; Xue, Xian; Li, Sen

doi:10.1016/j.geoderma.2018.05.038

Cited by 45 publications

(25 citation statements)

References 58 publications

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“…where T z is a tuning factor selected to produce a good climatological simulation and previous simulations set it equaled to 7.0 × 10 −4 , which resulted in a global annual dust emission of 1,500 Tg/a ( d < 10 μm; Zender & Newman, ); A z is the fraction of the erodible surface, which equal to 1 minus the vegetation cover and snow cover; S z is the source erodibility factor, which can be derived from topographic data by a revised method proposed by Du et al (); α z is the saltation bombardment efficiency that calculated by a method proposed by Marticorena and Bergametti () (Equation []); and Q is the horizontal saltation flux, kg/m/s.

α_{z} = M_{1} exp ([], ((), M_{2} η - M_{3}) ln 10),

where η is the percentage of clay that derived from soil data set and M 1 , M 2 , and M 3 are empirical coefficients.…”

Section: Methodsmentioning

confidence: 99%

“…To calculate the nutrients losses caused by wind erosion in Northern China, we collected meteorological data, land‐cover data, vegetation data, digital elevation model data, and snow depth data across Northern China (Table ). These data were first used to model the dust emission in Northern China, and the usage of each data set in the wind erosion model was detailed described in our previous study (Du et al, ).…”

Section: Methodsmentioning

confidence: 99%

“…In this study, a wind erosion model developed by us (Du et al, ) was employed to model the PM10 emission in Northern China. The model includes three submodels: threshold friction velocity for sand entrainment submodel (Equations and ), saltation submodel, and dust emission submodel.…”

Section: Methodsmentioning

confidence: 99%

“…data, digital elevation model data, and snow depth data across Northern China (Table 3). These data were first used to model the dust emission in Northern China, and the usage of each data set in the wind erosion model was detailed described in our previous study (Du et al, 2018).…”

Section: Data Preparationmentioning

confidence: 99%

“…Northern China is a hot spot for wind erosion; according to the previous researches, in Northern China, the total area that experiences wind erosion is 3.95 × 10 6 km 2 (MWR, ) and the dust emission about 130 Tg/a (Du, Wang, Xue, & Li, ). Such severe wind erosion results in massive losses of soils' nutrients.…”

Section: Introductionmentioning

confidence: 99%

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Estimation of soil organic carbon, nitrogen, and phosphorus losses induced by wind erosion in Northern China

Wang

Xue

et al. 2019

Land Degrad Dev

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The loss of nutrients induced by wind erosion causes serious land degradation. Northern China suffers from severe wind erosion that causes massive amounts of soil nutrients to be lost and results in land degradation. To thoroughly comprehend the mechanisms of land degradation in Northern China, the spatiotemporal distribution of nutrients losses induced by wind erosion must be considered. Therefore, in this study, a wind erosion model was employed to obtain the PM10 emissions in Northern China from 2001 to 2014, and the quantities of soil organic carbon (SOC), total nitrogen (TN), and total phosphorus (TP) entrained by PM10 were obtained using the integrated soil database of China. The results showed that the losses of SOC, TN, and TP induced by wind erosion were 0.894, 0.184, and 0.123 Tg/a, respectively, and the spatial distributions of these three nutrients differed from one another. According to the Moderate Resolution Imaging Spectroradiometer land‐cover data, the nutrients lost from desert ecosystems contributed the largest fractions of the total nutrients lost in Northern China, and the fractions of SOC, TN, and TP losses from the desert ecosystems all exceeded 50%. Following the desert ecosystems, the grassland ecosystems also had higher fractions of nutrients losses. The farmland ecosystems, which were the most severely impacted by human activities, contributed to less than 10% of the total nutrients losses.

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α_{z} = M_{1} exp ([], ((), M_{2} η - M_{3}) ln 10),

where η is the percentage of clay that derived from soil data set and M 1 , M 2 , and M 3 are empirical coefficients.…”

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Data Preparationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Estimation of soil organic carbon, nitrogen, and phosphorus losses induced by wind erosion in Northern China

Wang

Xue

et al. 2019

Land Degrad Dev

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Spatiotemporal variations and driving factors of the potential wind erosion rate in the Hexi region, PR China

et al. 2020

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To reduce the damage caused by wind erosion, the accurate evaluation of wind erosion dynamics and revelation of their driving mechanism are crucial. In this study, the revised wind erosion equation was applied for the estimation of the potential wind erosion rate (PWER) from 1982 to 2015 in the Hexi region, China. Geographic detection, variable control, and correlation analysis were used to determine the contributions of climatic factors and land use patterns to wind erosion. The results showed that the PWER decreased remarkably from 1982 to 2015 (annual average of 67.7 t ha −1 yr −1 for the entire region). Each year a severe and a mild wind erosion period occurred from October to May and from June to September, respectively. Spatially, the PWER was strong in the eastern, western, and northern regions (especially in the west) and less severe in the central and southern regions, and there was a decreasing tendency in 95% of the area. The PWER of Mongolia (north) was highest, while that of Minle was lowest. Climatic factors primarily determined the PWER in Hexi, among which wind speed was the main factor controlling the intensity of wind erosion. The area with a land use inhibiting wind erosion (3,240 km 2 ) was four times larger than that with a land use promoting wind erosion (800 km 2 ). Meanwhile, the total area with a changing land cover was less than 2% of the study area; therefore, this factor did not significantly affect the PWER in the short term. K E Y W O R D Sclimate change, Hexi region, land use and cover change, potential wind erosion rate, RWEQ

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Grazing effects on total carbon and nitrogen content of wind‐eroded soils in desert steppe

Zhang

et al. 2023

Land Degrad Dev

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A high stocking rate can intensify wind erosion in grasslands, and strong wind can carry away soil surface particles, soil carbon (C), and nitrogen (N), which leads to soil barrenness. In this research, the dust flux, total carbon (TC) and total nitrogen (TN) contents, and fluxes of aeolian sediment were determined in the nongrowing season (mid‐October to mid‐April of the following year) and growing season (mid‐April to mid‐October) from 2017 to 2020 at a continuous grazing gradient experiment platform established in 2004 in a desert steppe in Inner Mongolia, China. The results were as follows: (1) As the stocking rate increased, fluxes of aeolian sediment at 10 cm (H10), 30 cm (H30), and 100 cm (H100) were greatly increased (p < 0.05). Aeolian sediment fluxes followed the order control (CK) < light stocking rate (LG) < moderate stocking rate (MG) < heavy stocking rate (HG). (2) The TC and TN contents of aeolian sediment decreased with an increase in stocking rate, and higher grazing intensity resulted in a difference in TC content, which decreased between the two seasons. The TC flux/aeolian sediment flux increased with an increase in stocking rate, and the ratio of TC flux increased between two seasons due to the influence of heavy grazing. Grazing disturbance had little effect on TN flux. As grazing intensity increased, wind erosion resulted in an increase in soil available carbon loss, and this loss was more severe in the nongrowing season. (3) The C/N ratio increased with increase in aeolian sediment flux. The aeolian sediment flux and C/N showed an inverse relationship with the increase in grazing intensity. Regression lines for the two seasons showed an intersecting trend, and the intersection points moved backward as height increased, indicating that higher stocking rates could reduce the influence of grassland vegetation on C/N. As height increased, the regression intercept increased, indicating that the loss of wind‐eroded soil changed from a low C/N loss to a high C/N loss. In general, high stocking rates aggravated soil wind erosion, resulting in more C pool loss than N loss in terms of soil elements and more available C loss in the nongrowing season. In the nongrowing season, vegetation characteristics are poor, coupled with grazing interference, and wind erosion in the nongrowing season is serious in general; however, the change law of C and N in wind‐eroded soil is directly related to its particle size. C and N content in fine particles is higher, and C content in soil is much higher than N, so the TC loss is relatively large; therefore, reducing the intensity of grazing can reduce the occurrence of soil wind erosion, and implementing measures to protect grassland in spring and other periods vulnerable to wind erosion would be conducive to the sustainable usage of grassland resources.

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Modelling of sand/dust emission in Northern China from 2001 to 2014

Cited by 45 publications

References 58 publications

Estimation of soil organic carbon, nitrogen, and phosphorus losses induced by wind erosion in Northern China

Estimation of soil organic carbon, nitrogen, and phosphorus losses induced by wind erosion in Northern China

Spatiotemporal variations and driving factors of the potential wind erosion rate in the Hexi region, PR China

Grazing effects on total carbon and nitrogen content of wind‐eroded soils in desert steppe

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