PM10 emission from feedlots in soils with different texture: Cattle trampling effect

Oro, Laura Andrea de; Avecilla, Fernando; Panebianco, Juan Esteban; Buschiazzo, Daniel Eduardo

doi:10.1016/j.aeolia.2021.100742

Cited by 7 publications

(5 citation statements)

References 47 publications

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“…Dust emissions during cultivation are much higher compared to no-tillage measurements under similar environmental parameters, supporting measurements on arable land that found soil cultivation to dramatically increase total dust [31,32]. Another mechanical impulse affecting emission of TSP was found to originate from animal trampling, where the TSP increased with the increasing number of impacts and was found to be highest on unpaved roads [53].…”

Section: Discussionsupporting

confidence: 66%

Quantification of Dust Emissions during Tillage Operations in Steep Slope Vineyards in the Moselle Area

2022

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Measurements of dust emissions and the modeling of dissipation dynamics and total values are related to great uncertainties. Agricultural activity, especially soil cultivation, may be an essential component to calculate and model local and regional dust dynamics and even connect to the global dust cycle. To budget total dust and to assess the impact of tillage, measurement of mobilized and transported dust is an essential but rare basis. In this study, a simple measurement concept with Modified Wilson and Cook samplers was applied for dust measurements on a small temporal and spatial scale on steep-slope vineyards in the Moselle area. Without mechanical impact, a mean horizontal flux of 0.01 g m2 min−1 was measured, while row tillage produced a mean horizontal flux of 5.92 g m2 min−1 of mobilized material and 4.18 g m2 min−1 emitted dust from site (=soil loss). Compared on this singular-event basis, emissions during tillage operations generated 99.89% of total emitted dust from the site under low mean wind velocities. The results also indicate a differing impact of specific cultivation operations, mulching, and tillage tools as well as the additional influence of environmental conditions, with highest emissions on dry soil and with additional wind impact. The dust source function is strongly associated with cultivation operations, implying highly dynamic but also regular and thus predictable and projectable emission peaks of total suspended particles. Detailed knowledge of the effects of mechanical impulses and reliable quantification of the local dust emission inventory are a basis for analysis of risk potential and choice of adequate management options.

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Section: Discussionsupporting

confidence: 66%

Quantification of Dust Emissions during Tillage Operations in Steep Slope Vineyards in the Moselle Area

2022

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“…The following supporting information can be downloaded at: https: //www.mdpi.com/article/10.3390/atmos14111644/s1, Figure S1: Performance evaluation of the ANN model using a Taylor diagram involving RMSE and correlation coefficient for southern Xinjiang; Table S1: Summary of published studies related to soil-derived dust emission related to PM 10 and PM 2.5 fractions in recent five years; Table S2: Summary of published ANN studies related to soil erosion; Table S3: Percentage of different sized particles during the sand-storm on 23 April 2014 in Taklimakan Desert [71][72][73][74][75][76][77][78][79][80][81][82][83][84][85].…”

Section: Supplementary Materialsmentioning

confidence: 99%

Soil-Derived Dust PM10 and PM2.5 Fractions in Southern Xinjiang, China, Using an Artificial Neural Network Model

Gao,

Liu,

Zhang

et al. 2023

Atmosphere

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Soil-derived dust emissions have been widely associated with health and environmental problems and should therefore be accurately and reliably estimated and assessed. Of these emissions, the inhalable PM10 and PM2.5 are difficult to estimate. Consequently, to calculate PM10 and PM2.5 emissions from soil erosion, an approach based on an artificial neural network (ANN) model which provides a multilayered, fully connected framework that relates input parameters and outcomes was proposed in this study. Owing to the difficulty in obtaining the actual emissions of soil-derived PM10 and PM2.5 over a broad area, the PM10 and PM2.5 simulated results of the ANN model were compared with the published results simulated by the widely used wind erosion prediction system (WEPS) model. The PM10 and PM2.5 emission results, based on the WEPS, agreed well with the field data, with R2 values of 0.93 and 0.97, respectively, indicating the potential for using the WEPS results as a reference for training the ANN model. The calculated r, RMSE and MAE for the results simulated by the WEPS and ANN were 0.78, 3.37 and 2.31 for PM10 and 0.79, 1.40 and 0.91 for PM2.5, respectively, throughout Southern Xinjiang. The uncertainty of the soil-derived PM10 and PM2.5 emissions at a 95% CI was (−66–106%) and (−75–108%), respectively, in 2016. The results indicated that by using parameters that affect soil erodibility, including the soil pH, soil cation exchange capacity, soil organic content, soil calcium carbonate, wind speed, precipitation and elevation as input factors, the ANN model could simulate soil-derived particle emissions in Southern Xinjiang. The results showed that when the study domain was reduced from the entire Southern Xinjiang region to its five administrative divisions, the performance of the ANN improved, producing average correlation coefficients of 0.88 and 0.87, respectively, for PM10 and PM2.5. The performances of the ANN differed by study period, with the best result obtained during the sand period (March to May) followed by the nonheating (June to October) and heating periods (November to February). Wind speed, precipitation and soil calcium carbonate were the predominant input factors affecting particle emissions from wind erosion sources. The results of this study can be used as a reference for the wind erosion prevention and soil conservation plans in Southern Xinjiang.

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“…Soils are the main terrestrial reservoir of organic carbon (OC), which accumulates in the first centimetres of the soil. Lands used for agriculture and livestock are a large source of suspended dust containing OC (de Oro et al, 2021; Iturri et al, 2017). Particles with an aerodynamic diameter less than 10 μm (PM10, respirable dust) are emitted from topsoil layer by wind erosion, tillage and traffic.…”

Section: Introductionmentioning

confidence: 99%

Soil organic carbon enrichment in the particulate matter emitted by rural soils: A laboratory assessment

Ramirez Haberkon,

Mendez

2024

Land Degrad Dev

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The aim of this study was to assess the organic carbon (OC) content in the PM10 emitted by agricultural soils and rural roads under controlled conditions. Samples were collected from agricultural soils and rural roads. The PM10 was generated and collected using an electrostatic precipitator coupled with the Easy Dust Generator (EDG). This procedure ensures that the PM10 collected come specifically from soil. OC contents were measured in both the soil and PM10. The enrichment ratio (ER) was calculated as the ratio between OC content in the PM10 and OC content in the soil. The results showed that OC content in the PM10 ranged from 2.7% to 3.5% in agricultural soils and from 1.4% to 2.9% in rural roads. These values were comparable with the OC contents observed in fine particles transported by the wind, but lower than OC contents observed in PM10 samples collected in rural areas using active samplers and filters. A quadratic function described the association between OC in PM10 and OC in the soil. A negative potential function described the association between ERs and OC in the soil. Both associations suggested a saturation of OC in PM10 when the OC content in the soil was high. This information is crucial for a better comprehending of the dust emission role in the redistribution of OC within terrestrial ecosystems and to the atmosphere and oceans.

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PM10 emission from feedlots in soils with different texture: Cattle trampling effect

Cited by 7 publications

References 47 publications

Quantification of Dust Emissions during Tillage Operations in Steep Slope Vineyards in the Moselle Area

Quantification of Dust Emissions during Tillage Operations in Steep Slope Vineyards in the Moselle Area

Soil-Derived Dust PM10 and PM2.5 Fractions in Southern Xinjiang, China, Using an Artificial Neural Network Model

Soil organic carbon enrichment in the particulate matter emitted by rural soils: A laboratory assessment

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