Question

I want to paraphrase for this papers.

The purpose of this report introduces a useful tool, which estimates dust emission and dispersion. DUSTRAN is dust emission and transport model developed by Pacific Northwest National Laboratory. According to Shaw (2008), “(DUSTRAN), which calculates atmospheric dust concentrations that result from both natural and human activity.” We show three examples that it was applied to actual situations: dust concentration with observations of wind erosion in southeastern Washington, contaminated dust emission during high winds in southern Iraq, and transport of sea salt aerosols.

          First, a research group (Shaw, et al., 2008) shows both the DUSTRAN algorithm and the comparison of simulated dust concentration with data at the site. The measurements were made in southeastern Washington to monitor site recovering after a fire that occurred in 2001.The DUSTRAN has a dust emissions model for calculating emissions due to both natural and human activity. Moreover, it makes possible to get dust emission for specific particle size such as PM2.5, PM10, and so on. They also explain (Shaw, et al., 2008) the calculation of the atmospheric concentration of particulate matter caused by wind erosion, and it requires soil composition, characteristics of the soil crust vegetation cover, and soil moisture. They concluded that the comparisons had provided availability of the DUSTRAN as to estimate dust emission, however, they also suggested the importance of soil moisture data and the weakness of the DUSTRAN that it tends to overestimate PM10 when dust concentrations are low.

         Second, Zannetti, Daly, & Freedman (2015) applies it to air pollution problems at Qarmat-Ali, Basra, Iraq, during 2003. Before their study, the soil had been contaminated by sodium dichromate. Since people who worked at the site have claimed that their health was threatened by exposure to dust contaminating hexavalent chromium [Cr(VI)], they tried to build a model of the situation. To estimate the Cr(VI) concentration in the soil, they used the AERMOD model and the DUSTRAN model. The AERMOD model was used to calculate the ambient concentration of PM10/Cr(VI). While the AERMOD is widely used in the scientific field as a certain technique for estimating atmospheric transport of pollutants, including particulate matter and any material attached to particles, the author describes that “the AERMOD model is routinely used without any additional recalibration with local data, ...” (Zannetti, Daly, & Freedman, 2015). As an improvement of this point, they combined the DUSTRAN that determines the wind erosion at the local site with it. To calculate the emission rate of dust due to wind erosion, DUSTRAN gives a threshold value which depends on three parameters extracted from a local data: the soil moisture, the soil composition, and the surface roughness. If the wind velocity is larger than the value of the threshold, it assumes that dust is emitted from a source area. In addition to calculating the amount of the dust emission, DUSTRAN provides estimations of the particle size distribution in the dust. And then, DUSTRAN can estimate the amount of particulate matter contained in the dust emission. They finally concluded that they were able to perform a partial validation of the model which is combined generally used model (AERMOD) and the wind erosion process (DUSTRAN), by comparing the simulation outputs with measurement data at the site.

            Third, Jensen and his research group (Jensen, et al., 2016) proved the ability of DUSTRAN to model the transport of sea salt aerosols (SSA). By comparing their results from the DUSTRAN simulations with meteorological data taken at the near coast Maine Yankee Nuclear Power Plant (NPP) and the Environmental Protection Agency-measured CASTNET data from Acadia National Park (NP). As mentioned above DUSTRAN includes dispersion models, however, it is not specialized to a specific matter. The author tried to apply it and evaluate its potential for the modeling of chloride particulate matter by using one of the general dispersion models: CALPUFF which is suitable for mid-size domains of up to 200 km. The author concluded that “Comparisons of simulated and measured data have provided encouragement as to the potential practical value of DUSTRAN in predicting the dispersion of atmospheric chloride from the SSA” (Jensen, et al., 2016). The author mentioned, more experimental data and multiple data sets for DUSTRAN’s input may improve accuracy of a simulation. In conclusion, we have studied applications of DUSTRAN, a dust dispersion modeling system developed by Pacific Northwest National Laboratory, to actual problems: dust concentration with wind erosion in southeastern Washington, contaminated dust emission in southern Iraq, and transports of salt salt aerosols. Each research applied a general dispersion model included in the DUSTRAN system to simulate own situation, and proved the potential of it to estimate the concentration of dust containing an interesting matter such as hexavalent chloride, PM10, and chloride. To get precise results, however, these researches pointed out the importance of the local data measurements at the site. Because wind velocity and the soil moisture contribute to the emission rate simulation, local measurements at the site should be done carefully not to make lacks of data. Finally, as an application of DUSTRAN to nuclear study fields, it has a possibility to simulate an atmospheric transportation of dust containing a radionuclide after an accidental release from nuclear facilities. In this case, it also needs a local meteorological data, so tireless efforts of measurements are an essential factor for simulation.

References

Jensen, P., Tran, T., Fritz, B., Rutz, F., Ross, S., Gorton, A., . . . Trainor, K. (2016). Preliminary Evaluation of the DUSTRAN Modeling Suite for Modeling Atmospheric Chloride Transport. Air Quality, Atmosphere & Health,10(1), 25-31. doi:10.1007/s11869016-0404-5

Shaw, W. J., Allwine, K. J., Fritz, B. G., Rutz, F. C., Rishel, J. P., & Chapman, E. G. (2008). An evaluation of the wind erosion module in DUSTRAN. Atmospheric Environment,42(8), 1907-1921. doi:10.1016/j.atmosenv.2007.11.022

Zannetti, P., Daly, A. D., & Freedman, F. R. (2015). Dispersion modeling of particulate matter containing hexavalent chromium during high winds in southern Iraq. Journal of the Air & Waste Management Association, 65(2), 171-185. doi:10.1080/10962247.2014.981317

Answer 1

In this report, we will show the application of DUSTRAN, a dust emission, and dispersion transport modeling software. It is developed by pacific northwest National Laboratory. It is capable of calculating both natural and artificial dust contaminations. Here we will observe wind erosion in Washington, dust emission in Iraq, transport of sea salt aerosol.
The research groups set up the monitor site in Washington after recovering from a fire. They were able to monitor different particle size like PM 2.5, PM 10 etc. The concentration of particles generated by wind erosion was calculated. As per soil moisture data, vegetation of the area, dust particle data was classified. As a conclusion, they showed the cons of DUSTRAN as it emphasizes the data of PM 10.
At Basra in Iraq, the soil had been contaminated by dichromate of sodium. It affected the health of the local workers. The AERMOD and DUSTRAN model were used to estimate the transport of the pollutants including any other attached particulate matter. The DUSTRAN model calculated a threshold value based on the wind erosion data, soil composition, the surface condition of the area. DUSTRAN also showed the particle size distribution in the dust available. As a conclusion, they simulated the output by comparing the data acquired from AERMOD and DUSTRAN.
In 2016, the efficiency of DUSTRAN was proved by comparing the SSA (sea salt aerosol) data and an acquired data from NPP (Maine Yankee nuclear power plant). Though DUSTRAN expertise in the dispersion of specific matters, it was used to model the chlorides. The data were calibrated with the outputs of CALPUFF. This software is suitable for the medium sized area under 200km. In actual problems, more sets of data for the input may increase the efficiency of the model.
In each of the above cases, DUSTRAN was used along with a specific dispersion model. In each case, DUSTRAN proved its efficiency in the presentation of the dispersion models. The local measurements like soil moisture, wind velocity, emission rate are also very important. In the nuclear site, it is possible to simulate the transportation of the radio-nuclear particles after an accident in the nuclear plant. For this particular case, it requires many local meteorological data.