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Comparative inverse analysis of satellite (MODIS) and ground (PM10) observations to estimate dust emissions in East Asia

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Abstract

Soil dust aerosol is the largest contributor to aerosol mass concentrations in the troposphere and has considerable effects on air quality and climate. Arid and semi-arid areas of East Asia are one of the important dust source regions thus it is crucial to understand dust mobilization and accurately estimate dust emissions in East Asia. However, present dust models still contain large uncertainties with dust emissions that remain a significant contributor to the overall uncertainties in the model. In this study, we attempt to reduce these uncertainties by using an inverse modeling technique and obtain optimized dust emissions. We use Moderate Resolution Imaging Spectrometer (MODIS) aerosol optical depths (AODs) and groundbased mass concentrations of particles less than 10 μm in aerodynamic diameter (PM10) observations over East Asia in May 2007. The MODIS AODs are validated with AErosol RObotic NETwork (AERONET) AODs. The inversion uses the maximum a posteriori method and the GEOS-Chem chemical transport model (CTM) as a forward model. The model error is large over dust source regions including the Gobi Desert and Mongolia. We find that inverse modeling analyses from the MODIS and PM10 observations consistently result in decrease of dust emissions over Mongolia and the Gobi Desert. Whereas over the Taklamakan Desert and Manchuria, the inverse modeling analyses from both observations yield contrast results such as increase of dust sources using MODIS AODs, while decrease of those using PM10 observations. We discuss some limitations of both observations to obtain the optimized dust emissions and suggest several strategies for the improvement of dust emission estimates in the model.

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References

  • Abdou, W. A., D. J. Diner, J. V. Martonchik, C. J. Bruegge, R. A. Kahn, B. J. Gaitley, K. A. Crean, L. A. Remer, and B. Holben, 2005: Comparison of coincident multiangle imaging spectroradiometer and moderate resolution imaging spectroradiometer aerosol optical depths over land and ocean scenes containing aerosol robotic network sites. J. Geophys. Res., 110, D10S07.

    Article  Google Scholar 

  • Andreae, M. O., and P. Merlet, 2001: Emission of trace gases and aerosols from biomass burning. Global Biogeochem. Cycles, 15, 955–966.

    Article  Google Scholar 

  • Chin, M., and Coauthors, 2002: Tropospheric Aerosol optical thickness from the GOCART model and comparisons with satellite and sun photometer measurements. J. Atmos. Sci., 59, 461–483.

    Article  Google Scholar 

  • Choi, Y., R. J. Park, and C. Ho, 2009: Estimates of ground-level aerosol mass concentrations using a chemical transport model with Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol observations over East Asia. J. Geophys. Res., 114, D04204.

    Article  Google Scholar 

  • Chu, D. A., Y. J. Kaufman, C. Ichoku, L. A. Remer, D. Tanré, and B. N. Holben, 2002: Validation of MODIS aerosol optical depth retrieval over land. Geophys. Res. Lett., 29, 8007.

    Article  Google Scholar 

  • Donkelaar, A., R. V. Martin, R. C. Levy, A. M. Silva, M. Krzyzanowski, N. E. Chubarova, E. Semutnikova, and A. J. Cohen, 2011: Satellite-based estimates of ground-level fine particulate matter during extreme events: A case study of the Moscow fires in 2010. Atmos. Environ., 45, 6225–6232.

    Article  Google Scholar 

  • Fécan, F., B. Marticorena, and G. Bergametti, 1999: Parametrization of the increase of the aeolian erosion threshold wind friction velocity due to soil moisture for arid and semi-arid areas. Ann. Geophys., 17, 149–157.

    Google Scholar 

  • Fairlie, T. D., D. J. Jacob, and R. J. Park, 2007: The impact of transpacific transport of mineral dust in the United States. Atmos. Environ., 41, 1251–1266.

    Article  Google Scholar 

  • Feng, Q., P. Yang, G. W. Kattawar, C. N. Hsu, S. C. Tsay, and I. Laszlo, 2009: Effects of particle nonsphericity and radiation polarization on retrieving dust properties from MODIS observations. J. Atmos. Sci., 40, 776–789.

    Google Scholar 

  • Forster, P., and Coauthors, 2007: Changes in Atmospheric Constituents and in Radiative Forcing. Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.

    Google Scholar 

  • Ginoux, P., M. Chin, I. Tegen, J. M. Prospero, B. Holben, O. Dubovik, and S.-J. Lin, 2001: Sources and distributions of dust aerosols simulated with the GOCART model. J. Geophys. Res., 106, 20255–20273.

    Article  Google Scholar 

  • Gong, S. L., X. Y. Zhang, T. L. Zhao, I. G. McKendry, D. A. Jaffe, and N. M. Lu, 2003: Characterization of soil dust aerosol in China and its transport and distribution during 2001 ACE-Asia: 2. Model simulation and validation. J. Geophys. Res., 108, 4262.

    Article  Google Scholar 

  • Global Soil Data Task Group, 2000: Global gridded surfaces of selected soil characteristics (IGBP-DIS). Oak ridge national laboratory distributed active archive center, Oak Ridge, Tennessee, USA.

  • Hakami, A., D. K. Henze, J. H. Seinfeld, T. Chai, Y. Tang, G. R. Carmichael, and A. Sandu, 2005: Adjoint inverse modeling of black carbon during the Asian Pacific Regional Aerosol Characterization Experiment. J. Geophys. Res., 110, D14301.

    Article  Google Scholar 

  • Hara, Y., K. Yumimoto, I. Uno, A. Shimizu, N. Sugimoto, Z. Liu, and D. M. Winker, 2009: Asian dust outflow in the PBL and free atmosphere retrieved by NASA CALIPSO and an assimilated dust transport model. Atmos. Chem. Phys., 9, 1227–1239.

    Article  Google Scholar 

  • Henze, D. K., J. H. Seinfeld, and D. T. Shindell, 2009: Inverse modeling and mapping US air quality influences of inorganic PM2.5 precursor emissions using the adjoint of GEOS-Chem. Atmos. Chem. Phys., 9, 5877–5903.

    Article  Google Scholar 

  • Holben, B. N., and Coauthors, 1998: AERONET-A federated instrument network and data archive for aerosol characterization. Remote Sens. Environ., 66, 1–16.

    Article  Google Scholar 

  • Hsu, N. C., T. Si-Chee, M. D. King, and J. R. Herman, 2004: Aerosol properties over bright-reflecting source regions. T. Geosci. Remote Sens., 42, 557–569.

    Article  Google Scholar 

  • ____, S. C. Tsay, M. D. King, and J. R. Herman, 2006: Deep blue retrievals of Asian aerosol properties during ACE-Asia. T. Geosci. Remote Sens., 44, 3180–3195.

    Article  Google Scholar 

  • Huang, J., P. Minnis, H. Yan, Y. Yi, B. Chen, L. Zhang, and J. K. Ayers, 2010: Dust aerosol effect on semi-arid climate over Northwest China detected from A-Train satellite measurements. Atmos. Chem. Phys., 10, 6863–6872.

    Article  Google Scholar 

  • Ichoku, C., L. A. Remer, and T. F. Eck, 2005: Quantitative evaluation and intercomparison of morning and afternoon Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol measurements from Terra and Aqua. J. Geophys. Res., 110, D10S03.

    Article  Google Scholar 

  • Iwasaka, Y., and Coauthors, 2004: Pool of dust particles over the Asian Continent: Balloon-borne optical particle counter and ground-based lidar measurements at dunhuang, china. Environ. Monit. Assess., 92, 5–24.

    Article  Google Scholar 

  • Jacob, D. J., 2007: Lectures on inverse modeling. [available at http://acmg.seas.harvard.edu/education/jacob_lectures_inverse_modeling.pdf]

  • Jeong, J. I., R. J. Park, and D. Youn, 2008: Effects of Siberian forest fires on air quality in East Asia during May 2003 and its climate implication. Atmos. Environ., 42, 8910–8922.

    Article  Google Scholar 

  • Kopacz, M., D. J. Jacob, D. K. Henze, C. L. Heald, D. G. Streets, and Q. Zhang, 2009: Comparison of adjoint and analytical Bayesian inversion methods for constraining Asian sources of carbon monoxide using satellite (MOPITT) measurements of CO columns. J. Geophys. Res., 114, D04305.

    Article  Google Scholar 

  • Ku, B., and R. J. Park, 2011: Inverse modeling analysis of soil dust sources over East Asia. Atmos. Environ., 45, 5903–5912.

    Article  Google Scholar 

  • Liu, H., D. J. Jacob, I. Bey, and R. M. Yantosca, 2001: Constraints from 210Pb and 7Be on wet deposition and transport in a global three-dimensional chemical tracer model driven by assimilated meteorological fields. J. Geophys. Res., 106, 12,109–112,128.

    Google Scholar 

  • Marticorena, B., and G. Bergametti, 1995: Modeling the atmospheric dust cycle: 1. Design of a soil-derived dust emission scheme. J. Geophys. Res., 100, 16415–16430.

    Article  Google Scholar 

  • Palmer, P. I., D. J. Jacob, D. B. A. Jones, C. L. Heald, R. M. Yantosca, J. A. Logan, G. W. Sachse, and D. G. Streets, 2003: Inverting for emissions of carbon monoxide from Asia using aircraft observations over the western Pacific. J. Geophys. Res., 108, 8828.

    Article  Google Scholar 

  • Park, R. J., D. J. Jacob, B. D. Field, R. M. Yantosca, and M. Chin, 2004: Natural and transboundary pollution influences on sulfate-nitrateammonium aerosols in the United States: implications for policy. J. Geophys. Res., 109, D15204.

    Article  Google Scholar 

  • ____, _____, N. Kumar, and R. M. Yantosca, 2006: Regional visibility statistics in the United States: Natural and transboundary pollution influences, and implications for the Regional Haze Rule. Atmos. Environ., 40, 5405–5423.

    Article  Google Scholar 

  • Park, S.-U., A. Choe, E.-H. Lee, M.-S. Park, and X. Song, 2010: The Asian Dust Aerosol Model 2 (ADAM2) with the use of Normalized Difference Vegetation Index (NDVI) obtained from the Spot4/vegetation data. Theor. Appl. Climatol., 101, 191–208.

    Article  Google Scholar 

  • Prospero, J. M., 1999: Long-term measurements of the transport of African mineral dust to the southeastern United States: Implications for regional air quality. J. Geophys. Res., 104, 15917–15927.

    Article  Google Scholar 

  • Remer, L. A., and Coauthors, 2005: The MODIS aerosol algorithm, products, and validation. J. Atmos. Sci., 62, 947–973.

    Article  Google Scholar 

  • Rodgers, C. D., 2000: Inverse Methods for Atmospheric Sounding: Theory and Practice, World Sci., Hackensack, N. J., 238.

    Book  Google Scholar 

  • Seinfeld, J. H., and S. N. Pandis, 1998: Atmospheric Chemistry and Physics. Wiley, New York, 1326.

    Google Scholar 

  • Sekiyama, T. T., T. Y. Tanaka, A. Shimizu, and T. Miyoshi, 2010: Data assimilation of CALIPSO aerosol observations. Atmos. Chem. Phys., 10, 39–49.

    Article  Google Scholar 

  • Shao, Y., and Coauthors, 2003: Northeast Asian dust storms: Real-time numerical prediction and validation. J. Geophys. Res., 108, 4691.

    Article  Google Scholar 

  • Sokolik, I. N., and O. B. Toon, 1996: Direct radiative forcing by anthropogenic airborne mineral aerosols. Nature, 381, 681–683.

    Article  Google Scholar 

  • Sugimoto, N., Y. Hara, K. Yumimoto, I. Uno, M. Nishikawa, and J. Dulam, 2010: Dust emission estimated with an assimilated dust transport model using lidar network data and vegetation growth in the Gobi Desert in Mongolia. SOLA, 6, 125–128.

    Article  Google Scholar 

  • Tanaka, T. Y., and M. Chiba, 2005: Global simulation of dust aerosol with a chemical transport model, MASINGAR. J. Meteor. Soc. Japan, 83A, 255–278.

    Article  Google Scholar 

  • ____, and _____, 2006: A numerical study of the contributions of dust source regions to the global dust budget. Global Planet. Change, 52, 88–104.

    Article  Google Scholar 

  • Tang, J., Y. Xue, T. Yu, and Y. Guan, 2005: Aerosol optical thickness determination by exploiting the synergy of TERRA and AQUA MODIS. Remote Sens. Environ., 94, 327–334.

    Article  Google Scholar 

  • Tegen, I., 2003: Modeling the mineral dust aerosol cycle in the climate system. Quat. Sci. Rev., 22, 1821–1834.

    Article  Google Scholar 

  • ____, and A. A. Lacis, 1996: Modeling of particle size distribution and its influence on the radiative properties of mineral dust aerosol. J. Geophys. Res., 101, 19237–19244.

    Article  Google Scholar 

  • Torres, O., A. Tanskanen, B. Veihelmann, C. Ahn, R. Braak, P. K. Bhartia, P. Veefkind, and P. Levelt, 2007: Aerosols and surface UV products from Ozone monitoring instrument observations: An overview. J. Geophys. Res., 112, D24S47.

    Article  Google Scholar 

  • Uno, I., and Coauthors, 2004: Numerical study of Asian dust transport during the springtime of 2001 simulated with the Chemical Weather Forecasting System (CFORS) model. J. Geophys. Res., 109, D19S24.

    Article  Google Scholar 

  • ____, K. Yumimoto, A. Shimizu, Y. Hara, N. Sugimoto, Z. Wang, Z. Liu, and D. M. Winker, 2008: 3D structure of Asian dust transport revealed by CALIPSO lidar and a 4DVAR dust model. Geophys. Res. Lett., 35, L06803.

    Article  Google Scholar 

  • van der Werf, G. R., J. T. Randerson, L. Giglio, G. J. Collatz, P. S. Kasibhatla, and A. F. Arellano Jr, 2006: Interannual variability in global biomass burning emissions from 1997 to 2004. Atmos. Chem. Phys., 6, 3423–3441.

    Article  Google Scholar 

  • Wiscombe, W. J., 1980: Improved Mie scattering algorithms. Appl. Opt., 19, 1505–1509.

    Article  Google Scholar 

  • Wang, J., X. Xu, D. K. Henze, J. Zeng, Q. Ji, S.-C. Tsay, and J. Huang, 2012: Top-down estimate of dust emissions through integration of MODIS and MISR aerosol retrievals with the GEOS-Chem adjoint model. Geophys. Res. Lett., 39, L08802.

    Article  Google Scholar 

  • Yamada, M., and Coauthors, 2005: Feature of dust particles in the spring free troposphere over dunhuang in northwestern China: Electron microscopic experiments on individual particles collected with a balloonborne impactor. Water, Air Soil Pollut., 5, 231–250.

    Article  Google Scholar 

  • Yumimoto, K., I. Uno, N. Sugimoto, A. Shimizu, Z. Liu, and D. M. Winker, 2008: Adjoint inversion modeling of Asian dust emission using lidar observations. Atmos. Chem. Phys., 8, 2869–2884.

    Article  Google Scholar 

  • Zender, C. S., H. Bian, and D. Newman, 2003: Mineral Dust Entrainment and Deposition (DEAD) model: Description and 1990s dust climatology. J. Geophys. Res., 108, 4416.

    Article  Google Scholar 

  • Zhang, L., S. Gong, J. Padro, and L. Barrie, 2001: A size-segregated particle dry deposition scheme for an atmospheric aerosol module. Atmos. Environ., 35, 549–560.

    Article  Google Scholar 

  • ____, D. J. Jacob, M. Kopacz, D. K. Henze, K. Singh, and D. A. Jaffe, 2009: Intercontinental source attribution of ozone pollution at western U.S. sites using an adjoint method. Geophys. Res. Lett., 36, L11810.

    Article  Google Scholar 

  • Zhang, X. Y., S. L. Gong, T. L. Zhao, R. Arimoto, Y. Q. Wang, and Z. J. Zhou, 2003: Sources of Asian dust and role of climate change versus desertification in Asian dust emission. Geophys. Res. Lett., 30, 2272.

    Article  Google Scholar 

  • Zhao, T. L., S. L. Gong, X. Y. Zhang, and D. A. Jaffe, 2008: Asian dust storm influence on North American ambient PM levels: observational evidence and controlling factors. Atmos. Chem. Phys., 8, 2717–2728.

    Article  Google Scholar 

  • Zou, X. K., and P. M. Zhai, 2004: Relationship between vegetation coverage and spring dust storms over northern China. J. Geophys. Res., 109, D03104.

    Article  Google Scholar 

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Ku, B., Park, R.J. Comparative inverse analysis of satellite (MODIS) and ground (PM10) observations to estimate dust emissions in East Asia. Asia-Pacific J Atmos Sci 49, 3–17 (2013). https://doi.org/10.1007/s13143-013-0002-5

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  • DOI: https://doi.org/10.1007/s13143-013-0002-5

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