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Assessing the PM10 emission potential of sandy, dryland soils in South Africa using the PI-SWERL
Aeolian Research ( IF 3.1 ) Pub Date : 2021-09-13 , DOI: 10.1016/j.aeolia.2021.100747
Heleen C. Vos 1 , Wolfgang Fister 1 , Johanna R. von Holdt 2 , Frank D. Eckardt 2 , Anthony R. Palmer 3 , Nikolaus J. Kuhn 1
Affiliation  

The Free State has been identified as the region with the most dust sources in South Africa. These dust sources can be linked with the large, heavily cultivated cropland areas in this province, which leaves fields vulnerable to wind erosion after the harvest in the winter. For this study, the focus was on the factors that influence the emission from bare, flat surfaces on agricultural lands in this region. The Portable In-Situ Wind Erosion Laboratory (PI-SWERL) was used to measure the emission flux from adjacent crusted and loose surfaces, which was combined with shear strength, moisture, and soil texture measurements. Boosted regression tree (BRT) analyses were used to identify the variable with the highest relevance on the emission flux.

On the whole dataset, that the shear strength is the most important variable that controls the emission. This is reflected in the significantly lower emission from the crusted surfaces (0.49 mg m−2 s−1) compared to that of loose surfaces (2.34 mg m−2 s−1). However, for crusted surfaces, the presence of abraders appeared to be the most significant factor in emission, showing a power relationship between the abrader count and the emission flux (R2 = 0.76). In the case of the loose surfaces, the presence of clay and silt was a major influence in emissivity, with a linear relationship between the two variables (R2 = 0.68). This difference in factors depending on the agricultural disturbance, asks for a more holistic approach when predicting emission from such arid cropland areas.



中文翻译:

使用 PI-SWERL 评估南非沙质、旱地土壤的 PM10 排放潜力

自由州已被确定为南非灰尘源最多的地区。这些沙尘源可能与该省大量耕作的农田有关,这使得农田在冬季收割后易受风蚀。在这项研究中,重点是影响该地区农田裸露平坦表面排放的因素。便携式原位风蚀实验室 (PI-SWERL) 用于测量相邻结皮和松散表面的排放通量,并结合剪切强度、水分和土壤质地测量。使用增强回归树 (BRT) 分析来识别与排放通量具有最高相关性的变量。

在整个数据集上,剪切强度是控制发射的最重要变量。这反映在结壳表面(0.49 mg m -2 s -1)与松散表面(2.34 mg m -2 s -1)相比显着较低的发射。然而,对于结痂的表面,研磨器的存在似乎是排放中最重要的因素,显示出研磨器计数和排放通量之间的幂关系(R 2  = 0.76)。在松散表面的情况下,粘土和粉砂的存在是发射率的主要影响因素,两个变量之间呈线性关系(R 2 = 0.68)。这种取决于农业干扰的因素差异,要求在预测此类干旱农田地区的排放时采用更全面的方法。

更新日期:2021-09-13
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