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Observations of Asian Dust and Agricultural Fire Smoke Episodes: Transport and Impacts on Regional Air Quality in Southeast China

  • Yonghua Wu
  • Yong Han
  • Tijian Wang
Chapter
Part of the Springer Remote Sensing/Photogrammetry book series (SPRINGERREMO)

Abstract

This chapter presents an integrated observations of Asian dust and agricultural fire smoke episodes in spring and summer 2011 in Nanjing, China, using multiple satellites, ground-based sensors, and transport model. The source, long-range transport, time-height distribution, optical characteristics, and impacts on the air quality and visibility are demonstrated. The dust episode on May 1 shows two dust layers loading in the planetary-boundary-layer (PBL) and free troposphere originating from the Gobi deserts and Taklimakan deserts, respectively. The dust aerosols show the depolarization ratio of 0.1–0.2, optical depth (AOD) of 1.6 at 500-nm, and Angstrom exponents of 0.2. The hourly PM10 and PM2.5 concentrations show the maximum value of 767 μg/m3 and 222 μg/m3 thus indicating a heavy air pollution. The models are capable of simulating the right timing of dust transport event and primary loading in the PBL. For the episode of agricultural fires on June 3–4, the smoke aerosols are mainly located in the PBL with small depolarization ratio, and the AODs increase up to 3.0 with Angstrom exponent of 1.5–1.6. The PM10 and PM2.5 mass indicate a dramatic increase with the peak value reaching 800 μg/m3 and 485 μg/m3, respectively. The MODIS fire product shows the sources of agriculture fires located in the mid-east China (e.g., Jiangshu, Anhui, and Henan provinces). Regional transports are further illustrated by MODIS, OMI, and CALIPSO. Finally, the evaluations of MODIS-AOD and their correlation with the ground PM10 are illustrated in Nanjing urban area.

Keywords

Asian dust Smoke episodes Air quality China 

Notes

Acknowledgements

The authors gratefully acknowledge the dataset from the NASA satellites MODIS, AIRS, OMI CALIPSO and AERONET, NOAA Air Resources Laboratory (ARL) HYSPLIT model, NRL-NAAPS model teams, and Nanjing Environment Monitoring Center, China. This work was jointly supported by the NOAA # NA16SEC4810008, National Science Foundation of China (NSFC#) (Grant No. 41075012 and 40805006), and Natural Science Foundation of Jiangsu Province (Grant No. BE2015151).

References

  1. Ackerman AS, Toon OB, Stevens DE et al (2000) Reduction of tropical cloudiness by soot. Science 288:1042–1047CrossRefGoogle Scholar
  2. Badarinath KVS, Kharol SK, Latha KM, Chand TR, Prasad VK, Jyothsna AN, Samatha K (2007) Multiyear ground-based and satellite observations of aerosol properties over a tropical urban area in India. Atmos Sci Lett 8(1):7–13CrossRefGoogle Scholar
  3. Badarinath KVS, Kharol SK, Krishna Prasad V, Kaskaoutis DG, Kambezidis HD (2008) Variation in aerosol properties over Hyderabad, India during intense cyclonic conditions. Int J Remote Sens 29(15):4575–4597CrossRefGoogle Scholar
  4. Badarinath KVS, Sharma AR, Kharol SK, Prasad VK (2009) Variations in CO, O3 and black carbon aerosol mass concentrations associated with planetary boundary layer (PBL) over tropical urban environment in India. J Atmos Chem 62(1):73–86CrossRefGoogle Scholar
  5. Boersma K, Bucsela E, Brinksma E, Gleason J (2001) NO2, OMIEOS algorithm, Theoretical Basis Document: Trace gas algorithms: NO2, 4, 12–35Google Scholar
  6. Chen YX, Zhu B, Yi C et al (2014) A continuous air pollution event in Jianghus and Anhui Province based on satellite remote sensing and filed observations. China Enviorn Sci 34(4):827–836Google Scholar
  7. Cheng Z, Wang S, Fu X et al (2014) Impact of biomass burning on haze pollution in the Yangtze River delta, China: a case study in summer 2011. Atmos Chem Phys 14:4573–4585CrossRefGoogle Scholar
  8. Chin M, Diehl T, Ginoux P, Malm W (2007) Intercontinental transport of pollution and dust aerosols: implications for regional air quality. Atmos Chem Phys 7:5501–5517CrossRefGoogle Scholar
  9. Ding AJ, Fu CB, Yang XQ, Sun JN, Petäjä T, Kerminen, VM, Wang T, Xie Y, Herrmann E, Zheng LF, Nie W (2013) Intense atmospheric pollution modifies weather: a case of mixed biomass burning with fossil fuel combustion pollution in eastern China. Atmos Chem Phys 13:10545–10554Google Scholar
  10. Draxler RR, Hess GD (1997) Description of the HYSPLIT_4 modeling system. NOAA Tech. Memo. ERL ARL-224, NOAA Air Resources Laboratory, Silver Spring, MD, p 24Google Scholar
  11. Fischer EV, Hsu NC, Jaffe DA et al (2009) A decade of dust: Asian dust and springtime aerosol load in the U.S. Pacific Northwest. Geophys Res Lett 36:L03821.  https://doi.org/10.1029/2008GL036467 CrossRefGoogle Scholar
  12. Fu X, Wang SX, Cheng Z, Xing J et al (2014) Source, transport and impacts of a heavy dust event in the Yangtze River Delta, China in 2011. Atmos Chem Phys 14:1239–1254CrossRefGoogle Scholar
  13. Giglio L, Csiszar I, Justice C (2006) Global distribution and seasonality of active fires as observed with Terra and Aqua Moderated Resolution Imaging Spectroradiometer (MODIS) sensors. J Geophys Res 111:G02016.  https://doi.org/10.1029/2005JG000142 CrossRefGoogle Scholar
  14. Giles DM, Holben BN, Eck TF et al (2012) An analysis of AERONET aerosol absorption properties and classifications representative of aerosol source regions. J Geophys Res 117:D17203.  https://doi.org/10.1029/2012JD018127 CrossRefGoogle Scholar
  15. Han Y, Lü DR, Rao RZ, Wang YJ (2009) Determination of the complex refractive indices of aerosol from aerodynamic particle size spectrometer and integrating nephelometer measurements. Appl Opt 48(21):4108–4117CrossRefGoogle Scholar
  16. Han Y, Wu Y, Wang T et al (2015a) Characterizing a persistent Asian dust transport event: optical properties and impact on air quality through the ground-based and satellite measurements over Nanjing, China. Atmos Environ 115:304–316CrossRefGoogle Scholar
  17. Han Y, Wu Y, Wang T et al (2015b) Impacts of elevated-aerosol-layer and aerosol type on the correlation of AOD and particulate matter with ground-based and satellite measurements in Nanjing, Southeast China. Sci Total Environ 532:195–207CrossRefGoogle Scholar
  18. Hayasaka H, Noguchi I, Putra EI, Yulianti N, Vadrevu K (2014) Peat-fire-related air pollution in Central Kalimantan, Indonesia. Environ Pollut 195:257–266CrossRefGoogle Scholar
  19. He Q, Li C, Tang X et al (2010) Validation of MODIS derived aerosol optical depth over the Yangtze River Delta in China. Remote Sens Environ 114(8):1649–1661CrossRefGoogle Scholar
  20. Hoff RM, Christopher SA (2009) Remote sensing of particulate pollution from space: have we reached the Promised Land. J Air Waste Manage Assoc 59:645–675CrossRefGoogle Scholar
  21. Holben BN, Eck TF, Slutsker I et al (1998) AERONET—a federated instrument network and data archive for aerosol characterization. Remote Sens Environ 66:1–16CrossRefGoogle Scholar
  22. Huang XX, Wang TJ, Jiang F et al (2013) Studies on a severe dust storm in East Asia and its impact on the air quality of Nanjing, China. Aerosol Air Qual Res 13:179–193CrossRefGoogle Scholar
  23. Huang J, Wang T, Wang W, Li Z, Yan H (2014) Climate effects of dust aerosols over East Asian arid and semiarid regions. J Geophys Res Atmos 119:11,398–11,416CrossRefGoogle Scholar
  24. Ilan K, Kaufman YJ, Remer LA, Martins JV (2004) Measurement of the effect of Amazon smoke on inhibition of cloud formation. Science 303(5662):1342–1345CrossRefGoogle Scholar
  25. Intergovernmental Panel on Climate Change (IPCC) (2013) The Physical Science Basis, in Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. In: Stocker TF et al (eds) . Cambridge University Press, Cambridge, U. K., and New YorkGoogle Scholar
  26. Johnson BT, Shine KP, Forster PM (2004) The semi-direct aerosol effect: Impact of absorbing aerosols on marine stratocumulus. Quat J R Meteor Soc 130(599):1407–1422CrossRefGoogle Scholar
  27. Kant Y, Ghosh AB, Sharma MC, Gupta PK, Prasad VK, Badarinath KVS, Mitra AP (2000) Studies on aerosol optical depth in biomass burning areas using satellite and ground-based observations. Infrared Phys Technol 41(1):21–28CrossRefGoogle Scholar
  28. Le TH, Nguyen TNT, Lasko K, Ilavajhala S, Vadrevu KP, Justice C (2014) Vegetation fires and air pollution in Vietnam. Environ Pollut 195:267–275CrossRefGoogle Scholar
  29. Levy RC, Remer LA, Dubovik O (2007) Global aerosol optical properties and application to Moderate Resolution Imaging spectroradiometer aerosol retrieval over land. J Geophys Res 112:D13210.  https://doi.org/10.1029/2006JD007815 CrossRefGoogle Scholar
  30. Li HY, Han ZW, Cheng TT et al (2010a) Agricultural fire impacts on the air quality of Shanghai during Summer Harvesttime. Aerosol Air Qual Res 10(2):95–101CrossRefGoogle Scholar
  31. Li WJ, Shao LY, Buseck PR (2010b) Haze types in Beijing and the influence of agricultural biomass burning. Atmos Chem Phys 10:8119–8130.  https://doi.org/10.5194/acp-10-8119-2010 CrossRefGoogle Scholar
  32. Li G, Hu Y, Hu Q, Lin J, Li C, Chen J, Li L, Fu H (2014) Characteristics and chemical compositions of particulate matter collected at the selected metro stations of Shanghai, China. Sci Total Environ 496:443–452Google Scholar
  33. Liang Q, Jaeglé L, Jaffe DA et al (2004) Long-range transport of Asian pollution to the Northeast Pacific: Seasonal variations and transport pathways of carbon monoxide. J Geophys Res 109(D23):D23S07.  https://doi.org/10.1029/2003JD004402 CrossRefGoogle Scholar
  34. Liu M, Westphal DL, Wang S et al (2003) A high-resolution numerical study of the Asian dust storms of April 2001. J Geophys Res 108:D23.  https://doi.org/10.1029/2002JD003178 CrossRefGoogle Scholar
  35. Liu DY, Cao DF, Chen SY et al (2013) Effects of sand dust weather on air quality of cities in north bank of Taihu Lake. J Nat Disast 4:135–144Google Scholar
  36. Lu XB, Yu YY, Fu Y et al (2014) Characterization and identification method of ambient air quality influenced by straw burning. Environ Monitor Manage Tech 26(4):17–21Google Scholar
  37. National Research Council (2009) Global sources of local pollution: an assessment of long-range transport of key air pollutants to and from the United States. The National Academies Press, Washington, DCGoogle Scholar
  38. Ni H, Han Y, Cao J, et al (2015) Emission characteristics of carbonaceous particles and trace gases from open burning of crop residues in China, Atmos Environ.  https://doi.org/10.1016/j.atmosenv.2015.05.007.
  39. Pan L, Che H, Geng F et al (2010) Aerosol optical properties based on ground measurements over the Chinese Yangtze Delta Region. Atmos Environ 44:2587–2596CrossRefGoogle Scholar
  40. Prasad VK, Kant Y, Gupta PK, Elvidge C, Badarinath KVS (2002) Biomass burning and related trace gas emissions from tropical dry deciduous forests of India: a study using DMSP-OLS data and ground-based measurements. Int J Remote Sens 23(14):2837–2851CrossRefGoogle Scholar
  41. Prasad VK, Lata M, Badarinath KVS (2003) Trace gas emissions from biomass burning from northeast region in India—estimates from satellite remote sensing data and GIS. Environmentalist 23(3):229–236CrossRefGoogle Scholar
  42. Qu C, Li B, Wu H, Giesy JP (2012) Controlling air pollution from straw burning in China calls for efficient recycling. Environ Sci Technol 46:7934–7936CrossRefGoogle Scholar
  43. Streets D, Yarber K, Woo J, Carmichael K (2003) Biomass burning in Asia: annual and seasonal estimates and atmospheric emissions. Global Biogeochem Cycles 17(4):1099CrossRefGoogle Scholar
  44. Sugimoto N, Hara Y, Shimizu A et al (2011) Comparison of surface observations and a regional dust transport model assimilated with lidar network data in Asian Dust Event of March 29 to April 2, 2007. SOLA 7A:13–16.  https://doi.org/10.2151/sola.7A-004 CrossRefGoogle Scholar
  45. Susskind J, Barnet C, Blaisdell J (2003) Retrieval of atmospheric and surface parameters from AIRS/AMSU/HSB data in the presence of clouds. IEEE Geos Remote Sens (2):390–409Google Scholar
  46. Torres O, Tanskanen A, Veihelmann B et al (2007) Aerosols and surface UV products from Ozone Monitoring Instrument observations: an overview. J Geophys Res 112:D24S47.  https://doi.org/10.1029/2007JD008809 CrossRefGoogle Scholar
  47. Uno I, Wang Z, Chiba M et al (2006) Dust model intercomparison (DMIP) study over Asia: overview. J Geophys Res 111:D12213.  https://doi.org/10.1029/2005JD006575 CrossRefGoogle Scholar
  48. Vadrevu KP, Lasko K, Giglio L, Justice C (2014) Analysis of Southeast Asian pollution episode during June 2013 using satellite remote sensing datasets. Environ Pollut 195:245–256CrossRefGoogle Scholar
  49. Vadrevu KP, Lasko K, Giglio L, Justice C (2015) Vegetation fires, absorbing aerosols and smoke plume characteristics in diverse biomass burning regions of Asia. Environ Res Lett 10(10):105003CrossRefGoogle Scholar
  50. Wang TJ, Zhuang BL, Li S et al (2015a) The interactions between anthropogenic aerosols and the East Asian summer monsoon using RegCCMS. J Geophys Res Atmos 120:5602–5621CrossRefGoogle Scholar
  51. Wang LL, Xin J, Li X et al (2015b) The variability of biomass burning and its influence on regional aerosol properties during the wheat harvest season in North China. Atmos Res 157:153–163CrossRefGoogle Scholar
  52. Westphal DL, Curtis CA, Liu M, Walker AL (2009) Operational aerosol and dust storm forecasting. Earth Environ Sci 7.  https://doi.org/10.1088/1755-1307/7/1/012007
  53. Winker DM, Vaughan MA, Omar AH et al (2009) Overview of the CALIPSO mission and CALIOP data processing algorithms. J Atmos Ocean Technol 26:2310–2323CrossRefGoogle Scholar
  54. Wu Y, Cordero L, Gross B et al (2012) Smoke plume optical properties and transport observed by a multi-wavelength lidar, sunphotometer and satellite. Atmos Environ 63:32–42CrossRefGoogle Scholar
  55. Wu Y, Han Z, Nazmi C et al (2015) A trans-Pacific Asian dust episode and its impacts to air quality in the east coast of U.S. Atmos Environ 106:358–368CrossRefGoogle Scholar
  56. Xia X, Zong X, Sun L (2013) Exceptionally active agricultural fire season in mid-eastern China in June 2012 and its impact on the atmospheric environment. J Geophys Res 118:9889–9900Google Scholar
  57. Xie Y, Zhang Y, Xiong X et al (2011) Validation of MODIS aerosol optical depth product over China using CARSNET measurements. Atmos Environ 45(33):5970–5978CrossRefGoogle Scholar
  58. Yan X, Ohara T, Akimoto H (2006) Bottom-up estimate of biomass burning in mainland China. Atmos Environ 40:5362–5273CrossRefGoogle Scholar
  59. Zha Y, Wang Q, Yuan J et al (2011) Improved retrieval of aerosol optical thickness from MODIS measurements through derived surface reflectance over Nanjing, China. Tellus B 63:952–958CrossRefGoogle Scholar
  60. Zha S, Zhang S, Cheng T et al (2013) Agricultural fires and their potential impacts on regional air quality over China. Aerosol Air Qual Res 13:992–1001CrossRefGoogle Scholar
  61. Zhang XY, Wang YQ, Niu T (2012) Atmospheric aerosol compositions in China: spatial/temporal variability, chemical signature, regional haze distribution and comparisons with global aerosols. Atmos Chem Phys 12:779–799CrossRefGoogle Scholar
  62. Zhang T, Wooster MJ, Green DC et al (2015) New field-based agricultural biomass burning trace gas, PM2.5, and black carbon emission ratios and factors measured in situ at crop residue fires in Eastern China. Atmos Environ 121:22–34CrossRefGoogle Scholar
  63. Zhao T, Stowe L, Smirnov A et al (2002) Development of a global validation package for satellite oceanic aerosol optical thickness retrieval based on AERONET observations and its application to NOAA/NESDIS operational aerosol retrievals. J Atmos Sci 59:294–312CrossRefGoogle Scholar
  64. Zhu JL, Wang TJ, Xing L et al (2011) Analysis on the characteristic and mechanism of a heavy haze episode in Jiangshu Province, China. Environ Sci 31(12):1943–1950Google Scholar
  65. Zhuang BL, Wang TJ, Liu S et al (2014) Continuous measurement of black carbon aerosol in urban Nanjing of Yangtze River Delta, China. Atmos Environ 89:415–424CrossRefGoogle Scholar

Copyright information

© This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply 2018

Authors and Affiliations

  1. 1.NOAA-CREST at the City College of the City University of New YorkNew YorkUSA
  2. 2.School of Atmospheric ScienceNanjing UniversityNanjingChina

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