Detection of anthropogenic dust using CALIPSO lidar measurements
-
Published:2015-10-21
Issue:20
Volume:15
Page:11653-11665
-
ISSN:1680-7324
-
Container-title:Atmospheric Chemistry and Physics
-
language:en
-
Short-container-title:Atmos. Chem. Phys.
Author:
Huang J. P.ORCID, Liu J. J., Chen B., Nasiri S. L.
Abstract
Abstract. Anthropogenic dusts are those produced by human activities on disturbed soils, which are mainly cropland, pastureland, and urbanized regions, and are a subset of the total dust load which includes natural sources from desert regions. Our knowledge of anthropogenic dusts is still very limited due to a lack of data. To understand the contribution of anthropogenic dust to the total global dust load, it is important to identify it apart from total dust. In this study, a new technique for distinguishing anthropogenic dust from natural dust is proposed by using Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) dust and planetary boundary layer (PBL) height retrievals along with a land use data set. Using this technique, the global distribution of dust is analyzed and the relative contribution of anthropogenic and natural dust sources to regional and global emissions are estimated. Results reveal that local anthropogenic dust aerosol due to human activity, such as agriculture, industrial activity, transportation, and overgrazing, accounts for about 25 % of the global continental dust load. Of these anthropogenic dust aerosols, more than 53 % come from semi-arid and semi-wet regions. Annual mean anthropogenic dust column burden (DCB) values range from 0.42 g m−2, with a maximum in India, to 0.12 g m−2, with a minimum in North America. A better understanding of anthropogenic dust emission will enable us to focus on human activities in these critical regions and with such knowledge we will be more able to improve global dust models and to explore the effects of anthropogenic emission on radiative forcing, climate change, and air quality in the future.
Publisher
Copernicus GmbH
Subject
Atmospheric Science
Reference66 articles.
1. Angevine, W. M., White, A. B., and Avery, S. K.: Boundary-layer depth and entrainment zone characterization with a boundary-layer profiler, Bound.-Lay. Meteorol., 68, 375–385, https://doi.org/10.1007/BF00706797, 1994. 2. Bullard, J. E., Harrison, S. P., Baddock, M., Drake, N. A., Gill, T. E., McTainsh, G. H., and Sun, Y.: Preferential dust sources: A geomorphological classification designed for use in global dust-cycle models, J. Geophys. Res., 116, F04034, https://doi.org/10.1029/2011JF002061, 2011. 3. Chen, B., Huang, J., Minnis, P., Hu, Y., Yi, Y., Liu, Z., Zhang, D., and Wang, X.: Detection of dust aerosol by combining CALIPSO active lidar and passive IIR measurements, Atmos. Chem. Phys., 10, 4241–4251, https://doi.org/10.5194/acp-10-4241-2010, 2010. 4. Chen, S., Huang, J., Zhao, C., Qian, Y., Leung, L. R., and Yang, B.: Modeling the transport and radiative forcing of Taklamakan dust over the Tibetan Plateau: A case study in the summer of 2006, J. Geophys. Res., 118, 797–812, https://doi.org/10.1002/jgrd.50122, 2013. 5. Friedl, M. A., McIver, D. K., Hodges, J. C. F., Zhang, X. Y., Muchoney, D., Strahler, A. H., Woodcocka, C.E., Gopal, S., Schneider, A., Cooper, A., Baccini, A., Gao, F., and Schaaf, C.: Global land cover mapping from MODIS: Algorithms and early results, Remote Sens. Environ., 83, 287–302, 2002.
Cited by
112 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
|
|