scholarly journals A large source of dust missing in Particulate Matter emission inventories? Wind erosion of post-fire landscapes

Elem Sci Anth ◽  
2017 ◽  
Vol 5 ◽  
Author(s):  
N. S. Wagenbrenner ◽  
S. H. Chung ◽  
B. K. Lamb
Keyword(s):  
Particulate Matter ◽  
Wind Erosion ◽  
Dust Emission ◽  
Emission Model ◽  
Modeling Framework ◽  
Dust Emissions ◽  
Fire Scar ◽  
Large Source ◽  
Precipitation Regimes ◽  
Flux Measurements

Wind erosion of soils burned by wildfire contributes substantial particulate matter (PM) in the form of dust to the atmosphere, but the magnitude of this dust source is largely unknown. It is important to accurately quantify dust emissions because they can impact human health, degrade visibility, exacerbate dust-on-snow issues (including snowmelt timing, snow chemistry, and avalanche danger), and affect ecological and biogeochemical cycles, precipitation regimes, and the Earth’s radiation budget. We used a novel modeling approach in which local-scale winds were used to drive a high-resolution dust emission model parameterized for burned soils to provide a first estimate of post-fire PM emissions. The dust emission model was parameterized with dust flux measurements from a 2010 fire scar. Here we present a case study to demonstrate the ability of the modeling framework to capture the onset and dynamics of a post-fire dust event and then use the modeling framework to estimate PM emissions from burn scars left by wildfires in U.S. western sagebrush landscapes during 2012. Modeled emissions from 1.2 million ha of burned soil totaled 32.1 Tg (11.7–352 Tg) of dust as PM10 and 12.8 Tg (4.68–141 Tg) as PM2.5. Despite the relatively large uncertainties in these estimates and a number of underlying assumptions, these first estimates of annual post-fire dust emissions suggest that post-fire PM emissions could substantially increase current annual PM estimates in the U.S. National Emissions Inventory during high fire activity years. Given the potential for post-fire scars to be a large source of PM, further on-site PM flux measurements are needed to improve emission parameterizations and constrain these first estimates.

Measurement of wind erosion and dust emission triggered by different tillage tools

2021 ◽  
Author(s):  
Miriam Marzen ◽  
Thomas Iserloh ◽  
Matthias Porten ◽  
Johannes B. Ries
Keyword(s):  
Wind Erosion ◽  
Negative Impact ◽  
Management Practice ◽  
Dust Emission ◽  
Soil Surface ◽  
Soil Disturbance ◽  
Pests And Diseases ◽  
First Results ◽  
Flux Measurements ◽  
Mechanical Procedure

<p>Mechanized vineyard floor tillage aims at minimizing negative impact of weeds on water competition and spread of pests and diseases without herbicide application. It includes tillage between vines, in the vine row, and in headlands around vineyard blocks. While there is an increased awareness from vine growers and scientists concerning water erosion, wind erosion and dust emission are largely unnoticed processes that have not been investigated yet. The emission of soil particles seems to be strongly associated to the working of the soil surface by means of (tracked) tractor. This impact may be particularly important on surfaces considered erosion stable due to vegetation or stone cover preventing soil from direct detachment by wind.</p><p>The row-tillage only underneath the vines is an important management practice in modern and in organic viticulture because of the strongly reduced soil disturbance compared with clearing of the complete vineyard floor area. We investigated tillage as a trigger for wind erosion and dust production on particularly inclined vineyards in this study.</p><p>Three different tillage tools in three combinations were tested on two different steep-slope vineyards by means of modified Wilson and Cook Sampler (MWACS): rotary hoe, disc plow, and finger weeder.</p><p>We measured eroded material on both sites for different states of soil moisture and wind intensity. The results suggest a relationship between particular tillage tool combinations and airborne substrate particles that correspond to the general mechanical procedure.</p><p>These first results for measurement of tillage-induced wind erosion and dust emission indicate a considerable potential of vineyards to release dust that is related to specific management device needs to be investigated by means of qualitative analysis, flux measurements and monitoring.</p>

Crust formation on sandy savanna cropland soils and their potential to reduce dust emissions

2021 ◽  
Author(s):  
Heleen Vos ◽  
Wolfgang Fister ◽  
Frank Eckardt ◽  
Anthony Palmer ◽  
Nikolaus Kuhn
Keyword(s):  
South Africa ◽  
Wind Erosion ◽  
Dust Emission ◽  
Soil Surface ◽  
Free State ◽  
Management Approach ◽  
Crust Formation ◽  
Dust Emissions ◽  
Soil Crusts ◽  
The Impact

<p>After the conversion to cropland, dust emissions can lead to the degradation of agricultural soil. There are also offsite effects of dust emission due to the impact of dust on climate, human health, and global biogeochemistry. The sandy croplands in the Free State of South Africa have been identified by Eckardt et al. (2020) as one of the main dust sources in South Africa. The Free State is a semi-arid province that is dominated by grassland plains and 31% of the land is utilized for agriculture. The emission of dust from sandy Luvisols and Arenosols, which are typically used for crop farming, is mainly controlled by the cropping cycle. In general, the fields are left bare from at least July until December. When the fields have low surface roughness and stubble cover, the presence of physical soil crusts could be one of the main factors protecting the surface against wind erosion. Crusts can form before or during the growing season, before the vegetation cover is too extensive and protects the soil from raindrop impact. The aim of this study was to investigate the occurrence and strength of physical soil crusts on cropland soils in the Free State, to identify the rainfall required to form a stable crust, and to test their impact on dust emissions. Crust strength was measured using a fall cone penetrometer and a torvane, while laboratory rainfall simulations were used to form experimental crusts. Dust emissions from non-crusted and crusted soils were measured and compared with a Portable In-Situ Wind Erosion Laboratory (PI-SWERL).</p><p>Our results show that crusts with sufficient strength to limit dust emissions form on bare Arenosols and Luvisols in the field, illustrating their potential impact on dust emissions. The laboratory rainfall simulations showed that stable crusts could be formed on these soils by 15 mm of rainfall, which is a common amount for single events during the rainy season in the Free State. The PI-SWERL experiments illustrated that the PM10 emission flux of such crusted soils is between 0.14% and 0.26% of that of a non-crusted Luvisol and Arenosol, respectively. The presence of loose sand on the crust acts as an abrader and can increase the emissions up to 4% and 8 % of the non-crusted dust flux. Overall, our study shows that crusts in the field are potentially strong enough to protect the soil surfaces against wind erosion during a phase of the cropping cycle when the soil surface in not protected by plants. These conclusions are not limited to the converted grasslands in the Free State. This indicates that applying farming techniques on croplands that protect crusts or enhance crust formation could be considered as soil management approach to minimize dust emission from dryland sandy soils.</p>

scholarly journals Wind-Blown Dust Modeling Using a Backward-Lagrangian Particle Dispersion Model

2017 ◽  
Vol 56 (10) ◽  
pp. 2845-2867 ◽  
Author(s):  
Derek V. Mallia ◽  
Adam Kochanski ◽  
Dien Wu ◽  
Chris Pennell ◽  
Whitney Oswald ◽  
...  
Keyword(s):  
Dispersion Model ◽  
Meteorological Data ◽  
Dust Emission ◽  
Particle Dispersion ◽  
Emission Model ◽  
Dust Event ◽  
Lagrangian Particle ◽  
Modeling Framework ◽  
Source Regions ◽  
Dust Modeling

AbstractPresented here is a new dust modeling framework that uses a backward-Lagrangian particle dispersion model coupled with a dust emission model, both driven by meteorological data from the Weather Research and Forecasting (WRF) Model. This new modeling framework was tested for the spring of 2010 at multiple sites across northern Utah. Initial model results for March–April 2010 showed that the model was able to replicate the 27–28 April 2010 dust event; however, it was unable to reproduce a significant wind-blown dust event on 30 March 2010. During this event, the model significantly underestimated PM2.5 concentrations (4.7 vs 38.7 μg m−3) along the Wasatch Front. The backward-Lagrangian approach presented here allowed for the easy identification of dust source regions with misrepresented land cover and soil types, which required an update to WRF. In addition, changes were also applied to the dust emission model to better account for dust emitted from dry lake basins. These updates significantly improved dust model simulations, with the modeled PM2.5 comparing much more favorably to observations (average of 30.3 μg m−3). In addition, these updates also improved the timing of the frontal passage within WRF. The dust model was also applied in a forecasting setting, with the model able to replicate the magnitude of a large dust event, albeit with a 2-h lag. These results suggest that the dust modeling framework presented here has potential to replicate past dust events, identify source regions of dust, and be used for short-term forecasting applications.

scholarly journals An improved dust emission model – Part 1: Model description and comparison against measurements

2014 ◽  
Vol 14 (23) ◽  
pp. 13023-13041 ◽  
Author(s):  
J. F. Kok ◽  
N. M. Mahowald ◽  
G. Fratini ◽  
J. A. Gillies ◽  
M. Ishizuka ◽  
...  
Keyword(s):  
Large Scale ◽  
Friction Velocity ◽  
Climate Models ◽  
Dust Emission ◽  
Model Description ◽  
Emission Model ◽  
Threshold Friction Velocity ◽  
Dust Flux ◽  
Physically Based ◽  
Flux Measurements

Abstract. Simulations of the dust cycle and its interactions with the changing Earth system are hindered by the empirical nature of dust emission parameterizations in weather and climate models. Here we take a step towards improving dust cycle simulations by using a combination of theory and numerical simulations to derive a physically based dust emission parameterization. Our parameterization is straightforward to implement into large-scale models, as it depends only on the wind friction velocity and the soil's threshold friction velocity. Moreover, it accounts for two processes missing from most existing parameterizations: a soil's increased ability to produce dust under saltation bombardment as it becomes more erodible, and the increased scaling of the dust flux with wind speed as a soil becomes less erodible. Our treatment of both these processes is supported by a compilation of quality-controlled vertical dust flux measurements. Furthermore, our scheme reproduces this measurement compilation with substantially less error than the existing dust flux parameterizations we were able to compare against. A critical insight from both our theory and the measurement compilation is that dust fluxes are substantially more sensitive to the soil's threshold friction velocity than most current schemes account for.

scholarly journals The impact of measures to reduce ambient air PM<sub>10</sub> concentrations originating from road dust, evaluated for a street canyon in Helsinki

2019 ◽  
Vol 19 (17) ◽  
pp. 11199-11212 ◽  
Author(s):  
Ana Stojiljkovic ◽  
Mari Kauhaniemi ◽  
Jaakko Kukkonen ◽  
Kaarle Kupiainen ◽  
Ari Karppinen ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Street Canyon ◽  
Dust Emission ◽  
Road Dust ◽  
Ambient Air ◽  
Air Quality Measurements ◽  
Emission Models ◽  
The Impact ◽  
Quality Measurements

Abstract. We have numerically evaluated how effective selected potential measures would be for reducing the impact of road dust on ambient air particulate matter (PM10). The selected measures included a reduction of the use of studded tyres on light-duty vehicles and a reduction of the use of salt or sand for traction control. We have evaluated these measures for a street canyon located in central Helsinki for four years (2007–2009 and 2014). Air quality measurements were conducted in the street canyon for two years, 2009 and 2014. Two road dust emission models, NORTRIP (NOn-exhaust Road TRaffic Induced Particle emissions) and FORE (Forecasting Of Road dust Emissions), were applied in combination with the Operational Street Pollution Model (OSPM), a street canyon dispersion model, to compute the street increments of PM10 (i.e. the fraction of PM10 concentration originating from traffic emissions at the street level) within the street canyon. The predicted concentrations were compared with the air quality measurements. Both road dust emission models reproduced the seasonal variability of the PM10 concentrations fairly well but under-predicted the annual mean values. It was found that the largest reductions of concentrations could potentially be achieved by reducing the fraction of vehicles that use studded tyres. For instance, a 30 % decrease in the number of vehicles using studded tyres would result in an average decrease in the non-exhaust street increment of PM10 from 10 % to 22 %, depending on the model used and the year considered. Modelled contributions of traction sand and salt to the annual mean non-exhaust street increment of PM10 ranged from 4 % to 20 % for the traction sand and from 0.1 % to 4 % for the traction salt. The results presented here can be used to support the development of optimal strategies for reducing high springtime particulate matter concentrations originating from road dust.

scholarly journals Inverting the East Asian Dust Emission Fluxes Using the Ensemble Kalman Smoother and Himawari-8 AODs: A Case Study with WRF-Chem v3.5.1

Atmosphere ◽  
2019 ◽  
Vol 10 (9) ◽  
pp. 543
Author(s):  
Dai ◽  
Cheng ◽  
Goto ◽  
Schutgens ◽  
Kikuchi ◽  
...  
Keyword(s):  
Dust Emission ◽  
Asian Dust ◽  
Geostationary Satellite ◽  
Satellite Observations ◽  
Dust Emissions ◽  
Total Dust ◽  
Kalman Smoother ◽  
Independent Observations ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Horizontal And Vertical Distributions

We present the inversions (back-calculations or optimizations) of dust emissions for a severe winter dust event over East Asia in November 2016. The inversion system based on a fixed-lag ensemble Kalman smoother is newly implemented in the Weather Research and Forecasting model and is coupled with Chemistry (WRF-Chem). The assimilated observations are the hourly aerosol optical depths (AODs) from the next-generation geostationary satellite Himawari-8. The posterior total dust emissions (2.59 Tg) for this event are 3.8 times higher than the priori total dust emissions (0.68 Tg) during 25–27 November 2016. The net result is that the simulated aerosol horizontal and vertical distributions are both in better agreement with the assimilated Himawari-8 observations and independent observations from the ground-based AErosol RObotic NETwork (AERONET), the satellite-based Moderate Resolution Imaging Spectroradiometer (MODIS) and the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO). The developed emission inversion approach, combined with the geostationary satellite observations, can be very helpful for properly estimating the Asian dust emissions.

scholarly journals Why do models perform differently on particulate matter over East Asia? A multi-model intercomparison study for MICS-Asia III

2020 ◽  
Vol 20 (12) ◽  
pp. 7393-7410 ◽  
Author(s):  
Jiani Tan ◽  
Joshua S. Fu ◽  
Gregory R. Carmichael ◽  
Syuichi Itahashi ◽  
Zhining Tao ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
East Asia ◽  
Dust Emission ◽  
Sulfur Oxidation ◽  
Atmospheric Modeling ◽  
Weather Research And Forecasting ◽  
Forecasting Model ◽  
Air Quality Prediction ◽  
Weather Research

Abstract. This study compares the performance of 12 regional chemical transport models (CTMs) from the third phase of the Model Inter-Comparison Study for Asia (MICS-Asia III) on simulating the particulate matter (PM) over East Asia (EA) in 2010. The participating models include the Weather Research and Forecasting model coupled with Community Multiscale Air Quality (WRF-CMAQ; v4.7.1 and v5.0.2), the Regional Atmospheric Modeling System coupled with CMAQ (RAMS-CMAQ; v4.7.1 and v5.0.2), the Weather Research and Forecasting model coupled with chemistry (WRF-Chem; v3.6.1 and v3.7.1), Goddard Earth Observing System coupled with chemistry (GEOS-Chem), a non-hydrostatic model coupled with chemistry (NHM-Chem), the Nested Air Quality Prediction Modeling System (NAQPMS) and the NASA-Unified WRF (NU-WRF). This study investigates three model processes as the possible reasons for different model performances on PM. (1) Models perform very differently in the gas–particle conversion of sulfur (S) and oxidized nitrogen (N). The model differences in sulfur oxidation ratio (50 %) are of the same magnitude as that in SO42- concentrations. The gas–particle conversion is one of the main reasons for different model performances on fine mode PM. (2) Models without dust emission modules can perform well on PM10 at non-dust-affected sites but largely underestimate (up to 50 %) the PM10 concentrations at dust sites. The implementation of dust emission modules in the models has largely improved the model accuracies at dust sites (reduce model bias to −20 %). However, both the magnitude and distribution of dust pollution are not fully captured. (3) The amounts of modeled depositions vary among models by 75 %, 39 %, 21 % and 38 % for S wet, S dry, N wet and N dry depositions, respectively. Large inter-model differences are found in the washout ratios of wet deposition (at most 170 % in India) and dry deposition velocities (generally 0.3–2 cm s−1 differences over inland regions).

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