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[1] Ginoux, P., Prospero, J.M., Gill, T.E., Hsu, N.C. & Zhao, M., Global-scale attribution of anthropogenic and natural dust sources and their emission rates based on modis deep blue aerosol products, pp. 1–36, 2012.
[2] T womey, S. & Twomey, S., The influence of pollution on the shortwave albedo of clouds. Journal of the Atmospheric Sciences, 34(7), pp. 1149–1152, Jul. 1977.
[3] B aker, M.B., Corbin, R.G. & Latham, J., The influence of entrainment on the evolution of cloud droplet spectra: I. A model of inhomogeneous mixing. Quarterly Journal of the Royal Meteorological Society, 106(449), pp. 581–598, Jul. 1980.
[4] Albrecht, B.A., Aerosols, cloud microphysics, and fractional cloudiness. Science, 245(4923), pp. 1227–30, Sep. 1989.
[5] Ginoux, P., Prospero, J.M., Torres, O. & Chin, M., Long-term simulation of global dust distribution with the GOCART model: Correlation with North Atlantic Oscillation. Environmental Modelling and Software, 19(2), pp. 113–128, 2004.
[6] E ngelstaedter, S., Tegen, I. & Washington, R., North African dust emissions and transport. Earth-Science Reviews, 79(1–2), pp. 73–100, 2006.
[7] R izza, U. et al., WRF-Chem model simulations of a dust outbreak over the central Mediterranean and comparison with multi-sensor desert dust observations. Atmospheric Chemistry and Physics, 17(1), pp. 93–115, Jan. 2017.
[8] Gobbi, G.P., Kaufman, Y.J., Koren, I. & Eck, T.F., Classification of aerosol properties derived from AERONET direct sun data. Atmospheric Chemistry and Physics, 7(2), pp. 453–458, Jan. 2007.
[9] D eroubaix, A., Martiny, N., Chiapello, I. & Marticorena, B., Suitability of OMI aerosol index to reflect mineral dust surface conditions: Preliminary application for studying the link with meningitis epidemics in the Sahel. Remote Sensing of Environment, 133, pp. 116–127, 2013.
[10] D ubovik, O. & King, M.D., A flexible inversion algorithm for retrieval of aerosol optical properties from Sun and sky radiance measurements. Journal of Geophysical Research: Atmospheres, 105(D16), pp. 20673–20696, 2000.
[11] B ey, I. et al., Global modeling of tropospheric chemistry with assimilated meteorology: Model description and evaluation. Journal of Geophysical Research: Atmospheres, 106(D19), pp. 23073–23095, Oct. 2001.
[12] L amarque, J.F. et al., CAM-chem: Description and evaluation of interactive atmospheric chemistry in the Community Earth System Model. Geoscientific Model Development, 5(2), pp. 369–411, Mar. 2012.
[13] Gelaro, R. et al., The modern-era retrospective analysis for research and applications, version 2 (MERRA-2). Journal of Climate, 30(14), pp. 5419–5454, Jul. 2017.
[14] Grell, G.A. et al., Fully coupled ‘online’ chemistry within the WRF model. Atmospheric Environment, 39(37), pp. 6957–6975, 2005.
[15] F ast, J.D. et al., Evolution of ozone, particulates, and aerosol direct radiative forcing in the vicinity of Houston using a fully coupled meteorology-chemistry-aerosol model. Journal of Geophysical Research: Atmospheres, 111(21), p. D21305, Nov. 2006.
[16] B asart, S. et al., Extensive comparison between a set of European dust regional models and observations in the Western Mediterranean for the summer 2012 Pre-ChArMEx/TRAQA campaign. in Air Pollution Modeling and its Application XXIV, Cham:Springer, pp. 79–83, 2016.
[17] H uneeus, N. et al., Global dust model intercomparison in AeroCom phase i. Atmospheric Chemistry and Physics, 11(15), pp. 7781–7816, Aug. 2011.
[18] R izza, U. et al., Sensitivity of WRF-Chem model to land surface schemes: Assessment in a severe dust outbreak episode in the Central Mediterranean (Apulia Region). Atmospheric Research, 201(August 2017), pp. 168–180, 2017.
[19] T anaka, T.Y. & Chiba, M., A numerical study of the contributions of dust source regions to the global dust budget. Global and Planetary Change, 52(1–4), pp. 88–104, Jul. 2006.
[20] Ginoux, P. et al., Sources and distributions of dust aerosols simulated with the GOCART model. Journal of Geophysical Research: Atmospheres, 106(D17), pp. 20255–20273, Sep. 2001.
[21] P rospero, J.M., Ginoux, P., Torres, O., Nicholson, S.E. & Gill, T.E., Environmental characterization of global sources of atmospheric soil dust identified with the Nimbus 7 Total Ozone Mapping Spectrometer (TOMS ) absorbing aerosol product. Reviews of Geophysics, 40(1), p. 1002, Feb. 2002.
[22] Washington, R. et al., African climate change: Taking the shorter route. Bulletin of the American Meteorological Society, 87(10), pp. 1355–1366, Oct. 2006.
[23] K oren, I. et al., The Bodélé depression: A single spot in the Sahara that provides most of the mineral dust to the Amazon forest. Environmental Research Letters, 1(1), p. 014005, Oct. 2006.
[24] K allos, G. et al., Ten-year operational dust forecasting – Recent model development and future plans. IOP Conference Series: Earth and Environmental Science, 7(1), p. 012012, Mar. 2009.
[25] M oulin, C. et al., Satellite climatology of African dust transport in the Mediterranean atmosphere. Journal of Geophysical Research: Atmospheres, 103(D11), pp. 13137–13144, Jun. 1998.
[26] D ee, D.P. et al., The ERA-Interim reanalysis: Configuration and performance of the data assimilation system. Quarterly Journal of the Royal Meteorological Society, 137(656), pp. 553–597, Apr. 2011.
[27] K umar, R., Barth, M.C., Pfister, G.G., Naja, M. & Brasseur, G.P., WRF-Chem simulations of a typical pre-monsoon dust storm in northern India: Influences on aerosol optical properties and radiation udget. Atmospheric Chemistry and Physics, 14(5), pp. 2431–2446, Mar. 2014.
[28] M orrison, H., Thompson, G. & Tatarskii, V., Impact of cloud microphysics on the development of trailing stratiform precipitation in a simulated squall line: Comparison of one- and two-moment schemes,” Monthly Weather Review, 137(3), pp. 991–1007, Mar. 2009.
[29] I acono, M.J., Delamere, J.S., Mlawer, E.J., Shephard, M.W., Clough, S.A. & Collins, W.D., Radiative forcing by long-lived greenhouse gases: Calculations with the AER radiative transfer models. Journal of Geophysical Research: Atmospheres, 113(13), p. D13103, Jul. 2008.
[30] N akanishi, M. & Niino, H., An improved Mellor–Yamada Level-3 model: Its numerical stability and application to a regional prediction of advection fog. Boundary-Layer Meteorology, 119(2), pp. 397–407, May 2006.
[31] N iu, G.Y. et al., The community Noah land surface model with multiparameterization options (Noah-MP): 1. Model description and evaluation with local-scale measurements. Journal of Geophysical Research: Atmospheres, 116(12), p. D12109, Jun. 2011.
[32] Grell, G.A. & Freitas, S.R., A scale and aerosol aware stochastic convective parameterization for weather and air quality modeling. Atmospheric Chemistry and Physics, 14(10), pp. 5233–5250, May 2014.
[33] E mmons, L.K. et al., Description and evaluation of the Model for Ozone and Related chemical Tracers, version 4 (MOZART -4). Geoscientific Model Development, 3(1), pp. 43–67, 2010.
[34] Z averi, R.A., Easter, R.C., Fast, J.D. & Peters, L.K., Model for Simulating Aerosol Interactions and Chemistry (MOSAIC). Journal of Geophysical Research: Atmospheres, 113(13), pp. 1–29, 2008.
[35] Wiedinmyer, C. et al., The Fire INventory from NCAR (FINN): A high resolution global model to estimate the emissions from open burning. Geoscientific Model Development, 4(3), pp. 625–641, 2011.
[36] K alnay, E. et al., The NCEP/NCAR 40-year reanalysis project. Bulletin of the American Meteorological Society, 77(3), pp. 437–471, Mar. 1996.
[37] F écan, F., Marticorena, B. & Bergametti, G., Parametrization of the increase of the aeolian erosion threshold wind friction velocity due to soil moisture for arid and semiarid areas. Annales Geophysicae, 17(1), pp. 149–157, 1999.
[38] S alomonson, V.V., Barnes, W.L., Maymon, P.W., Montgomery, H.E. & Ostrow, H., MODIS: Advanced facility instrument for studies of the Earth as a system. IEEE Transactions on Geoscience and Remote Sensing, 27(2), pp. 145–153, Mar. 1989.
[39] H olben, B.N. et al., AERONET —A federated instrument network and data archive for aerosol characterization. Remote Sensing of Environment, 66(1), pp. 1–16, Oct. 1998.
[40] S hen, S., Ostrenga, D. & Vollmer, B., Long-term global aerosol products from NASA reanalysis MERRA-2 Available at GES DISC. American Geophysical Union Fall Meeting 2015, Abstract id. A31D-0095, 2015.
[41] C hang, J.S. et al., A three-dimensional Eulerian acid deposition model: Physical concepts and formulation. Journal of Geophysical Research, 92(12), p. 14681, Dec. 1987.
[42] R izza, U., Anabor, V., Mangia, C., Miglietta, M.M., Degrazia, G.A. & Passerini, G., WRF-chem simulation of a Saharan dust outbreak over the Mediterranean regions,”Ciência e Nature, 38(0), p. 330, Jul. 2016.
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Open Access
Research article

A Preliminary Assessment of Mineral Dust Outbreaks in Italian Coastal Cities

Mauro Morichetti1,
Giorgio Passerini1,
Simone Virgili1,
Enrico Mancinelli1,
Umberto Rizza2
1
Department of Industrial Engineering and Mathematical Science, Marche Polytechnic University, Ancona, Italy
2
Institute of Atmospheric Sciences and Climate, National Research Council of Italy, Lecce, Italy
International Journal of Environmental Impacts
|
Volume 3, Issue 2, 2020
|
Pages 132-142
Received: N/A,
Revised: N/A,
Accepted: N/A,
Available online: N/A
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Abstract:

The Mediterranean region, being the area well known for its predominantly mild climate, has been subject to human intervention for millennia. The fast population growth and its intense rural and transportation activities are the main responsible factors that contribute to increasing anthropogenic airborne pollutant emissions. In addition to anthropogenic emissions, the area is influenced also by natural emissions such as episodes of wind-blown mineral dust from the Sahara desert. In order to assess and speciate the growing emissions over the Mediterranean region, we used WRF-Chem chemical transport model. One-year modellings based on two distinct simulations, have been carried out: the first considering only mineral dust (‘DUSTONLY’ simulation) and the second one considering othertypes of emissions, such as biogenic and anthropogenic (‘MOZMOSAIC’ simulation). Both simulations use the Goddard Chemistry Aerosol Radiation and Transport dust emission scheme. The National Centers for Environmental Prediction (NCEP)/National Center for Atmospheric Research (NCAR) reanalysis data were used to assess the accuracy of simulated meteorological fields such as temperature, relative humidity and wind speed and direction, showing a great capability of WRF-Chem to model the experimental fields and their spatial trends. The comparison between the modelled dust column mass density and the same field calculated through the corresponding Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA2) reanalysis showed an evident dust load overestimate over North Africa. Such overestimate is confirmed by the comparison of both simulations with the AERONET aerosol optical depth (AOD) (550 nm) products: Rome and Naples stations have nearly the same trend and AOD peaks are captured well, but the dust concentrations are overestimated from both simulations

Keywords: Dust outbreak, GOCART dust emission, MOZART chemistry, MOSAIC aerosol, WRF-Chem
References
[1] Ginoux, P., Prospero, J.M., Gill, T.E., Hsu, N.C. & Zhao, M., Global-scale attribution of anthropogenic and natural dust sources and their emission rates based on modis deep blue aerosol products, pp. 1–36, 2012.
[2] T womey, S. & Twomey, S., The influence of pollution on the shortwave albedo of clouds. Journal of the Atmospheric Sciences, 34(7), pp. 1149–1152, Jul. 1977.
[3] B aker, M.B., Corbin, R.G. & Latham, J., The influence of entrainment on the evolution of cloud droplet spectra: I. A model of inhomogeneous mixing. Quarterly Journal of the Royal Meteorological Society, 106(449), pp. 581–598, Jul. 1980.
[4] Albrecht, B.A., Aerosols, cloud microphysics, and fractional cloudiness. Science, 245(4923), pp. 1227–30, Sep. 1989.
[5] Ginoux, P., Prospero, J.M., Torres, O. & Chin, M., Long-term simulation of global dust distribution with the GOCART model: Correlation with North Atlantic Oscillation. Environmental Modelling and Software, 19(2), pp. 113–128, 2004.
[6] E ngelstaedter, S., Tegen, I. & Washington, R., North African dust emissions and transport. Earth-Science Reviews, 79(1–2), pp. 73–100, 2006.
[7] R izza, U. et al., WRF-Chem model simulations of a dust outbreak over the central Mediterranean and comparison with multi-sensor desert dust observations. Atmospheric Chemistry and Physics, 17(1), pp. 93–115, Jan. 2017.
[8] Gobbi, G.P., Kaufman, Y.J., Koren, I. & Eck, T.F., Classification of aerosol properties derived from AERONET direct sun data. Atmospheric Chemistry and Physics, 7(2), pp. 453–458, Jan. 2007.
[9] D eroubaix, A., Martiny, N., Chiapello, I. & Marticorena, B., Suitability of OMI aerosol index to reflect mineral dust surface conditions: Preliminary application for studying the link with meningitis epidemics in the Sahel. Remote Sensing of Environment, 133, pp. 116–127, 2013.
[10] D ubovik, O. & King, M.D., A flexible inversion algorithm for retrieval of aerosol optical properties from Sun and sky radiance measurements. Journal of Geophysical Research: Atmospheres, 105(D16), pp. 20673–20696, 2000.
[11] B ey, I. et al., Global modeling of tropospheric chemistry with assimilated meteorology: Model description and evaluation. Journal of Geophysical Research: Atmospheres, 106(D19), pp. 23073–23095, Oct. 2001.
[12] L amarque, J.F. et al., CAM-chem: Description and evaluation of interactive atmospheric chemistry in the Community Earth System Model. Geoscientific Model Development, 5(2), pp. 369–411, Mar. 2012.
[13] Gelaro, R. et al., The modern-era retrospective analysis for research and applications, version 2 (MERRA-2). Journal of Climate, 30(14), pp. 5419–5454, Jul. 2017.
[14] Grell, G.A. et al., Fully coupled ‘online’ chemistry within the WRF model. Atmospheric Environment, 39(37), pp. 6957–6975, 2005.
[15] F ast, J.D. et al., Evolution of ozone, particulates, and aerosol direct radiative forcing in the vicinity of Houston using a fully coupled meteorology-chemistry-aerosol model. Journal of Geophysical Research: Atmospheres, 111(21), p. D21305, Nov. 2006.
[16] B asart, S. et al., Extensive comparison between a set of European dust regional models and observations in the Western Mediterranean for the summer 2012 Pre-ChArMEx/TRAQA campaign. in Air Pollution Modeling and its Application XXIV, Cham:Springer, pp. 79–83, 2016.
[17] H uneeus, N. et al., Global dust model intercomparison in AeroCom phase i. Atmospheric Chemistry and Physics, 11(15), pp. 7781–7816, Aug. 2011.
[18] R izza, U. et al., Sensitivity of WRF-Chem model to land surface schemes: Assessment in a severe dust outbreak episode in the Central Mediterranean (Apulia Region). Atmospheric Research, 201(August 2017), pp. 168–180, 2017.
[19] T anaka, T.Y. & Chiba, M., A numerical study of the contributions of dust source regions to the global dust budget. Global and Planetary Change, 52(1–4), pp. 88–104, Jul. 2006.
[20] Ginoux, P. et al., Sources and distributions of dust aerosols simulated with the GOCART model. Journal of Geophysical Research: Atmospheres, 106(D17), pp. 20255–20273, Sep. 2001.
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[23] K oren, I. et al., The Bodélé depression: A single spot in the Sahara that provides most of the mineral dust to the Amazon forest. Environmental Research Letters, 1(1), p. 014005, Oct. 2006.
[24] K allos, G. et al., Ten-year operational dust forecasting – Recent model development and future plans. IOP Conference Series: Earth and Environmental Science, 7(1), p. 012012, Mar. 2009.
[25] M oulin, C. et al., Satellite climatology of African dust transport in the Mediterranean atmosphere. Journal of Geophysical Research: Atmospheres, 103(D11), pp. 13137–13144, Jun. 1998.
[26] D ee, D.P. et al., The ERA-Interim reanalysis: Configuration and performance of the data assimilation system. Quarterly Journal of the Royal Meteorological Society, 137(656), pp. 553–597, Apr. 2011.
[27] K umar, R., Barth, M.C., Pfister, G.G., Naja, M. & Brasseur, G.P., WRF-Chem simulations of a typical pre-monsoon dust storm in northern India: Influences on aerosol optical properties and radiation udget. Atmospheric Chemistry and Physics, 14(5), pp. 2431–2446, Mar. 2014.
[28] M orrison, H., Thompson, G. & Tatarskii, V., Impact of cloud microphysics on the development of trailing stratiform precipitation in a simulated squall line: Comparison of one- and two-moment schemes,” Monthly Weather Review, 137(3), pp. 991–1007, Mar. 2009.
[29] I acono, M.J., Delamere, J.S., Mlawer, E.J., Shephard, M.W., Clough, S.A. & Collins, W.D., Radiative forcing by long-lived greenhouse gases: Calculations with the AER radiative transfer models. Journal of Geophysical Research: Atmospheres, 113(13), p. D13103, Jul. 2008.
[30] N akanishi, M. & Niino, H., An improved Mellor–Yamada Level-3 model: Its numerical stability and application to a regional prediction of advection fog. Boundary-Layer Meteorology, 119(2), pp. 397–407, May 2006.
[31] N iu, G.Y. et al., The community Noah land surface model with multiparameterization options (Noah-MP): 1. Model description and evaluation with local-scale measurements. Journal of Geophysical Research: Atmospheres, 116(12), p. D12109, Jun. 2011.
[32] Grell, G.A. & Freitas, S.R., A scale and aerosol aware stochastic convective parameterization for weather and air quality modeling. Atmospheric Chemistry and Physics, 14(10), pp. 5233–5250, May 2014.
[33] E mmons, L.K. et al., Description and evaluation of the Model for Ozone and Related chemical Tracers, version 4 (MOZART -4). Geoscientific Model Development, 3(1), pp. 43–67, 2010.
[34] Z averi, R.A., Easter, R.C., Fast, J.D. & Peters, L.K., Model for Simulating Aerosol Interactions and Chemistry (MOSAIC). Journal of Geophysical Research: Atmospheres, 113(13), pp. 1–29, 2008.
[35] Wiedinmyer, C. et al., The Fire INventory from NCAR (FINN): A high resolution global model to estimate the emissions from open burning. Geoscientific Model Development, 4(3), pp. 625–641, 2011.
[36] K alnay, E. et al., The NCEP/NCAR 40-year reanalysis project. Bulletin of the American Meteorological Society, 77(3), pp. 437–471, Mar. 1996.
[37] F écan, F., Marticorena, B. & Bergametti, G., Parametrization of the increase of the aeolian erosion threshold wind friction velocity due to soil moisture for arid and semiarid areas. Annales Geophysicae, 17(1), pp. 149–157, 1999.
[38] S alomonson, V.V., Barnes, W.L., Maymon, P.W., Montgomery, H.E. & Ostrow, H., MODIS: Advanced facility instrument for studies of the Earth as a system. IEEE Transactions on Geoscience and Remote Sensing, 27(2), pp. 145–153, Mar. 1989.
[39] H olben, B.N. et al., AERONET —A federated instrument network and data archive for aerosol characterization. Remote Sensing of Environment, 66(1), pp. 1–16, Oct. 1998.
[40] S hen, S., Ostrenga, D. & Vollmer, B., Long-term global aerosol products from NASA reanalysis MERRA-2 Available at GES DISC. American Geophysical Union Fall Meeting 2015, Abstract id. A31D-0095, 2015.
[41] C hang, J.S. et al., A three-dimensional Eulerian acid deposition model: Physical concepts and formulation. Journal of Geophysical Research, 92(12), p. 14681, Dec. 1987.
[42] R izza, U., Anabor, V., Mangia, C., Miglietta, M.M., Degrazia, G.A. & Passerini, G., WRF-chem simulation of a Saharan dust outbreak over the Mediterranean regions,”Ciência e Nature, 38(0), p. 330, Jul. 2016.
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MLA Style
Chicago Style
GB-T-7714-2015
Morichetti, M., Passerini, G., Virgili, S., Mancinelli, E., & Rizza, U. (2020). A Preliminary Assessment of Mineral Dust Outbreaks in Italian Coastal Cities. Int. J. Environ. Impacts., 3(2), 132-142. https://doi.org/10.2495/EI-V3-N2-132-142
M. Morichetti, G. Passerini, S. Virgili, E. Mancinelli, and U. Rizza, "A Preliminary Assessment of Mineral Dust Outbreaks in Italian Coastal Cities," Int. J. Environ. Impacts., vol. 3, no. 2, pp. 132-142, 2020. https://doi.org/10.2495/EI-V3-N2-132-142
@research-article{Morichetti2020APA,
title={A Preliminary Assessment of Mineral Dust Outbreaks in Italian Coastal Cities},
author={Mauro Morichetti and Giorgio Passerini and Simone Virgili and Enrico Mancinelli and Umberto Rizza},
journal={International Journal of Environmental Impacts},
year={2020},
page={132-142},
doi={https://doi.org/10.2495/EI-V3-N2-132-142}
}
Mauro Morichetti, et al. "A Preliminary Assessment of Mineral Dust Outbreaks in Italian Coastal Cities." International Journal of Environmental Impacts, v 3, pp 132-142. doi: https://doi.org/10.2495/EI-V3-N2-132-142
Mauro Morichetti, Giorgio Passerini, Simone Virgili, Enrico Mancinelli and Umberto Rizza. "A Preliminary Assessment of Mineral Dust Outbreaks in Italian Coastal Cities." International Journal of Environmental Impacts, 3, (2020): 132-142. doi: https://doi.org/10.2495/EI-V3-N2-132-142
MORICHETTI M， PASSERINI G， VIRGILI S， et al. A Preliminary Assessment of Mineral Dust Outbreaks in Italian Coastal Cities[J]. International Journal of Environmental Impacts， 2020， 3(2)： 132-142. https://doi.org/10.2495/EI-V3-N2-132-142