Atmos. Chem. Phys., 19, 11843–11864, 2019 https://doi.org/10.5194/acp-19-11843-2019 © Author(s) 2019. This work is distributed under the Creative Commons Attribution 4.0 License. Spatial distribution of aerosol microphysical and optical properties and direct radiative effect from the China Aerosol Remote Sensing Network Huizheng Che1, Xiangao Xia2,3, Hujia Zhao1,4, Oleg Dubovik5, Brent N. Holben6, Philippe Goloub5, Emilio Cuevas-Agulló7, Victor Estelles8, Yaqiang Wang1, Jun Zhu9, Bing Qi10, Wei Gong11, Honglong Yang12, Renjian Zhang13, Leiku Yang14, Jing Chen15, Hong Wang1, Yu Zheng1, Ke Gui1, Xiaochun Zhang16, and Xiaoye Zhang1 1State Key Laboratory of Severe Weather (LASW) and Key Laboratory of Atmospheric Chemistry (LAC), Chinese Academy of Meteorological Sciences, CMA, Beijing, 100081, China 2Laboratory for Middle Atmosphere and Global Environment Observation (LAGEO), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China 3School of the Earth Science, University of Chinese Academy of Science, Beijing, 100049, China 4Environmental and Meteorological Department, Institute of Atmospheric Environment, CMA, Shenyang, 110016, China 5Laboratoire d’Optique Amosphérique, Université des Sciences et Technologies de Lille, 59655, Villeneuve d’Ascq, France 6NASA Goddard Space Flight Center, Greenbelt, MD, USA 7Centro de Investigación Atmosférica de Izaña, AEMET, 38001 Santa Cruz de Tenerife, Spain 8Dept. Fisica de la Terra i Termodinamica, Universitat de València, C/ Dr. Moliner 50, 46100 Burjassot, Spain 9Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science & Technology, Nanjing, 210044, China 10Hangzhou Meteorological Bureau, Hangzhou, 310051, China 11State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, 430079, China 12Shenzhen Meteorological Bureau, Shenzhen, 518040, China 13Key Laboratory of Regional Climate-Environment Research for Temperate East Asia, Institute of Atmospheric Physics, Beijing, 100029, China 14School of Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo, 454000, China 15Shijiazhuang Meteorological Bureau, Shijiazhuang, 050081, China 16Meteorological Observation Center, CMA, Beijing, 100081, China Correspondence: Huizheng Che ([email protected]) and Xiaoye Zhang ([email protected]) Received: 27 April 2019 – Discussion started: 28 May 2019 Revised: 11 August 2019 – Accepted: 23 August 2019 – Published: 24 September 2019 Abstract. Multi-year observations of aerosol microphysical tical depth at 440 nm (AOD440 nm) increased from remote and optical properties, obtained through ground-based re- and rural sites (0.12) to urban sites (0.79), and the ex- mote sensing at 50 China Aerosol Remote Sensing Network tinction Ångström exponent (EAE440–870 nm) increased from (CARSNET) sites, were used to characterize the aerosol cli- 0.71 at the arid and semi-arid sites to 1.15 at the urban matology for representative remote, rural, and urban areas sites, presumably due to anthropogenic emissions. Single- over China to assess effects on climate. The annual mean ef- scattering albedo (SSA440 nm) ranged from 0.88 to 0.92, in- fective radii for total particles (ReffT) decreased from north dicating slightly to strongly absorbing aerosols. Absorption to south and from rural to urban sites, and high total parti- AOD440 nm values were 0.01 at the remote sites versus 0.07 cle volumes were found at the urban sites. The aerosol op- at the urban sites. The average direct aerosol radiative ef- Published by Copernicus Publications on behalf of the European Geosciences Union. 11844 H. Che et al.: Ground-based AOP and direct radiative efect from CARSNET fect (DARE) at the bottom of atmosphere increased from ropean aerosol Lidar Network (EARLINET; Pappalardo et the sites in the remote areas (−24:40 W m−2) to the urban al., 2014); and the Global Atmosphere Watch Programmer- areas (−103:28 W m−2), indicating increased cooling at the Precision Filter Radiometers network (GAW-PFR; Wehrli, latter. The DARE for the top of the atmosphere increased 2002; Estellés et al., 2012). The China Aerosol Remote Sens- from −4:79 W m−2 at the remote sites to −30:05 W m−2 ing NETwork (CARSNET), the Chinese Sun Hazemeter Net- at the urban sites, indicating overall cooling effects for the work (CSHNET), and the Sun–Sky Radiometer Observation Earth–atmosphere system. A classification method based on Network (SONET) have been established to measure aerosol SSA440 nm, fine-mode fraction (FMF), and EAE440–870 nm optical properties in China (Che et al., 2009a, 2015; Xin et showed that coarse-mode particles (mainly dust) were dom- al., 2007, 2015; Li et al., 2018). Furthermore, aerosol optical inant at the rural sites near the northwestern deserts, while properties have also been used in comprehensive studies of light-absorbing, fine-mode particles were important at most aerosol physical characteristics and chemical composition in urban sites. This study will be important for understanding many regions of China (Che et al., 2009c, 2018; Zhao et al., aerosol climate effects and regional environmental pollution, 2018). and the results will provide useful information for satellite China has become one of the largest aerosol sources in validation and the improvement of climate modelling. the world associated with its rapid economic development, and this has caused significant effects on local environments and regional climate (Che et al., 2005; Xia, 2010; Li et al., 2016; Yang et al., 2018, 2019b; Zhao et al., 2019; Gui et 1 Introduction al., 2019). There have been numerous studies that have fo- cused on aerosol optical properties obtained though ground- Atmospheric aerosols have important direct effects on cli- based remote-sensing methods in China (Luo et al., 2002; Li mate because they can scatter and absorb radiant energy and, et al., 2003; Duan and Mao, 2007). Some previous research in so doing, affect the Earth’s energy balance (Charlson et al., has paid more attention to aerosol’s optical properties and its 1992; Yang et al., 2016). Meanwhile, the aerosols can serve radiative effects over the urban industrial areas, as well as at as cloud condensation nuclei or ice nuclei to affect the cli- coastal sites in northeastern and eastern China (Wang et al., mate indirectly through aerosol–cloud interactions (Twomey 2010; Xin et al., 2011; Xia et al., 2007; Zhao et al., 2016; Wu et al., 1984; Garrett and Zhao, 2006; Zhao et al., 2015; Xie et et al., 2012; Shen et al., 2019). Many studies of aerosol op- al., 2013). The optical properties of the aerosol determine the tical properties were conducted in northern China with high particles’ direct effects on the Earth’s radiative balance and aerosol loadings, such as the Beijing–Tianjin–Hebei region weather–climate change (Ramanathan et al., 2001; Eck et al., (Che et al., 2014; Xia et al., 2013; Fan et al., 2006; Xie et 2005; Myhre, 2009; Zhao et al., 2018; Che et al., 2019a; al., 2008; Zhang et al., 2019; Yang et al., 2019a; Zhao et al., Li et al., 2016). Aerosol optical depth (AOD) is one of the 2018; Zheng et al., 2019). Aerosol optical properties have key measures of the total aerosol extinction effects on cli- also been investigated at Hefei, Shouxian, Nanjing, Taihu, mate (Breon et al., 2002), and the extinction Ångström expo- Shanghai, and other sites in eastern China (Lee et al., 2010; nent (EAE), with spectral dependence, can be used to obtain He et al., 2012; Zhuang et al., 2014; Z. Wang et al., 2015; the information about aerosol size distributions (Gobbi et al., Che et al., 2018). Some studies of aerosol optical properties 2007; Eck et al., 1999; Zheng et al., 2017). The aerosols’ have been made in southern and central China (L. C. Wang absorptivity depends on particle composition and is a key et al., 2015; Tao et al., 2014b), and those at remote and rural determinant to calculate the direct aerosol radiative effect sites in China provide information on regional background (Haywood and Shine, 1995; Li et al., 2016), and the single- conditions (Che et al., 2009b; Wang et al., 2010; Zhu et al., scattering albedo (SSA) is a parameter that has the spectral 2014; Yuan et al., 2014). dependence to distinguish major aerosol particle types (Ja- China’s vast size, varied terrain, and heterogeneity of cobson et al., 2000; Dubovik et al., 2002; Gelencser, 2004; aerosol sources has led to strong temporal and spatial vari- Russell et al., 2010; Giles et al., 2012). ability in aerosol optical and physical properties. The mix- With the recognition of the importance for climate, tures of aerosol types at most sites are complex, and aerosol the aerosol optical properties have been obtained from populations’ sizes and compositions are affected by their ground-based monitoring networks worldwide; some of sources, transformations that occur during transportation, the major networks include, the Aerosol Robotic Network and removal processes (Cao et al., 2007; Wang et al., 2007; (AERONET; Holben et al., 1998) and its sub-networks, the Zhang et al., 2013; Wan et al., 2015). National-scale, ground- PHOtométrie pour le Traitement Opérationnel de Normalisa- based measurements of aerosol microphysical and optical tion Satellitaire (PHOTONS), the Canadian Sun Photometer properties obtained from the sun photometer provide a better Network (AEROCAN), and the Iberian Network for aerosol understanding of the aerosols’ climate effects over the differ- measurements (RIMA; Goloub et al., 2007; Bokoye et al., ent regions of China. The measurements of greatest interest 2001; Prats et al., 2011); the SKYrad Network (SKYNET; include aerosol size distributions (volume and aerosol effec- Takamura and Nakajima, 2004; Che et al., 2008); the Eu- tive radii) and optical properties (AOD, AE, SSA, absorption Atmos. Chem. Phys., 19, 11843–11864, 2019 www.atmos-chem-phys.net/19/11843/2019/ H. Che et al.: Ground-based AOP and direct radiative efect from CARSNET 11845 AOD) because those data can be used to evaluate aerosol di- cated at 28.31◦ N, 16.50◦ W (2391.0 m a.s.l.), in conjunction rect radiative effect.