Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | ce, ffi , , 5 1 14 , Y. Ma 9 , Y. Wang 5 , and G. Shi 13 , X. Deng 8 , H. Zhao 4 , Q. Chen 13 , R. Zhang 7 , B. Holben 3 12715 12716 , J. Yu 2 , B. Damiri 4 , J. Zhu , P. Goloub 12 2 , B. Qi , L. Blarel 1 , X. Xia 11 1 , H. Wang , F. Geng 6 10 , X. Zhang 1 School of Atmospheric Sciences, NanjingShanghai University, Hankou Urban Rd. Environmental 22, Meteorology Nanjing Center, 210093, Pudong China New Area Weather O Hangzhou Meteorological Bureau, Hangzhou 310051,Plateau China Atmospheric and Environment Key Laboratory of Sichuan Province, State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical This discussion paper is/has beenand under Physics review (ACP). for Please the refer journal to Atmospheric the Chemistry corresponding final paper in ACP if available. Key Laboratory of Atmospheric Chemistry (LAC), Chinese Academy of Meteorological Laboratory for Middle Atmosphere and Global Environment Observation (LAGEO), Laboratoire d’Optique Amosphérique, Université des Sciences et Technologies de Lille, Biospheric Sciences Branch, Code 923, NASA/Goddard Space Flight Center,Institute Greenbelt, of Atmos. Environ., ChinaMeteorological Meteorological Observation Administration, Center, Shenyang CMA, 110016, Beijing, China 100081, China Cimel électronique, Paris, 75011, France Key Laboratory of Regional Climate-Environment for Temperate East Asia (RCE-TEA), Institute of Tropical and Marine Meteorology/Guangdong Provincial Key Laboratory of 1 Sciences (CAMS), CMA,2 Beijing, 100081, China Institute of Atmospheric3 Physics, Chinese Academy of Sciences, Beijing, 100029,59655 China Villeneuve d’Ascq,4 France MD, USA 5 6 7 8 Institute of Atmospheric9 Physics, Chinese Academy of Sciences, Beijing 100029,Regional China Numerical Weather Prediction,10 CMA, Guangzhou 510080, China 11 X. Zhang T. Wang SMB, Shanghai 200135, China 12 13 College of Atmospheric Sciences, ChengduChengdu University 610225, of China Information14 Technology, Fluid Dynamics (LASG), Institute ofBeijing, Atmospheric 100029, Physics, China Chinese Academy of Sciences, Received: 20 March 2015 – Accepted: 15Correspondence April to: 2015 H. – Che Published: ([email protected]) 29 AprilPublished 2015 by Copernicus Publications on behalf of the European Geosciences Union. Ground-based aerosol climatology of China: aerosol optical depths fromChina the Aerosol Remote Sensing Network (CARSNET) 2002–2013 H. Che Atmos. Chem. Phys. Discuss., 15, 12715–12776,www.atmos-chem-phys-discuss.net/15/12715/2015/ 2015 doi:10.5194/acpd-15-12715-2015 © Author(s) 2015. CC Attribution 3.0 License. Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 0.20) < erent cal- ff ect the local ff 0.60) in central 0.80) compared > < 1.20 over the southern reaches > 12718 12717 ects on radiative fluxes (Holben et al., 2001). ff erent instruments, and more often than not, used di ff from 2009 to 2013. 1 ects on regional weather and climate and also human health (Che − ff 0.03 yr ∼ erent times with di ff Satellite monitoring and ground-based observations are two important ways for mon- China is the most populated and largest developing country in the world, and it has Ground-based sunphotometers were first used to retrieve aerosol optical data in acterize the ambient aerosol,pollution, (2) (3) address validate satellite larger retrievals questionsvestigate and aerosol numerical concerning and modeling environmental cloud algorithms, e and (4) in- due to the copious industrialSeinfeld emissions et and frequent al., dust 2004; events Li (Huebert et et al., al., 2003; 2007). These aerosol particles not only a region and eastern coast regionet of China, al., etc. 2001; (Wang Zhang and et Qiu,provided al., 1988; valuable information Li 2002; on et Xia al., local etat 1995; aerosol al., Hu di optical 2005; properties, Tan but et they al., were 2009). carried These studies have itoring the Earth’s aerosolmeasurement properties networks are long-term especially (Holbensensed useful et for data al., validating (Holben and 2001).networks augmenting Ground-based et have remotely- al., been established; 2001).works these of So AERONET include (Holben the far et al., Cimel(Bokoye several 1998), et sunphotometer al., PHOTONS automatic (Goloub 2001), based et RIMA robotic al., net- (PratsKim 2008), et ground-based AEROCAN al., et 2011), al., the 2004; skyradiotometer network Uchiyamaand (SKYNET, so et on. al., Information 2005), on the aerosoltribute optical WMO to properties GAWPFR our obtained Network understanding from (Wehrli, of these 2002), the networks con- earth’s systems because it can be used to (1) char- become one of the largest global sources for aerosol particles and their precursors China in the earlythen, 1980s there (Zhao have et been al., manyhave 1983; investigations been Qiu into conducted et in aerosol al., north optical 1983; China, properties, northeast Mao and China, et studies Tibet al., Plateau, 1983). northwest Since desert atmospheric environment but also areand transported beyond to (Streets the et East al., Asiacause 2001; and Eck significant Pacific et e regions al., 2005)et where al., the transported 2005; materials Liang can and Xia, 2005; Xia, 2010; Chen et al., 2011). Abstract Long-term measurements of aerosol(Alpha) optical made for depths CARSNET (AOD) wereerties and compiled for into Angstrom China. a exponents Quality-assured climatologyresenting monthly of remote, mean aerosol rural, AODs optical and are prop- urbanat presented areas. remote for AODs stations, 50 were rural/desert sites 0.14, regions,and rep- 0.34, the Loess urban 0.42, Plateau, 0.54, sites, central and and respectively,0.82, 0.74 eastern and 1.19, China, the and corresponding 1.05. Alpha AODs values increased were from north 0.97, 0.55, to south, with low values ( over the Tibetan Plateauand and eastern northwestern China where China industrialsources. and emissions AODs high and were AODs anthropogenic 0.20–0.40 ( activitiesareas were in in likely semi-arid north and and arid northeast regions China. and Alphas some background were of the Yangtze Riverdeserts and and industrial at parts clean of northeast sites China, in Alphas northeastern were lower China. ( In the northwestern with central and easternduring regions. summer, Dust and biomass eventsern in burning and spring, contribute eastern the hygroscopicincreased China. particle high The AODs, growth especially AODs in show north- decreasing trends from 2006 to 2009 but ter (PM) can scattertion, or size, etc. absorb (Charlson solar et(Hansen radiation, al., et 1992) depending al., and on 1997). causecent Despite the either years, the large-scale particles’ aerosol numerous cooling optical composi- or studies propertiesin warming that are current have still been assessments one conducted and ofHansen in the predictions et largest re- of al., sources global 2000; of climatic Ramanathan uncertainty et change al., (IPCC, 2001). 2013, 2007; 1 Introduction Aerosol particles are important for global and regional climate because particulate mat- 5 5 10 15 25 20 10 15 25 20 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 40 ∼ erent regions in China and ff 12720 12719 cult to characterize regional and temporal variations in aerosol optical ffi erent regions of China, and (3) an analysis of the monthly AODs at 440 nm and the The primary objective of this paper is to present a climatology of aerosol optical The China Aerosol Research Network (CARSNET) is a ground-based network for Ground-based networks for measuring aerosol optical properties in China were first ff article include: (1) a description(2) of an the evaluation sites, of datadi processing, the and spatial data quality characteristics control, of AOD and Angstrom exponent over CARSNET results, monthly and yearly averagesites AODs and are Alphas provided for the as 50investigations Appendix CARSNET of tables. aerosols, We climate, and hope the this atmospheric database environment will of be China. used for future properties developed from CARSNETstudy measurements characterizes made the from spatial 2002using data to and from 2013. temporal 50 This variations CARSNETrural sites of and with urban aerosol at regions optical least of one properties China year are of all measurements. represented Remote, in the study. The contents of this Angstrom exponents between 440 tothe 870 nm long-term (Alpha) (12 at yr) all variations 50 of sites, AOD (4) a at discussion 12 of CARSNET sites. To provide a record of AERONET and PHOTONS sites);piece_of_map_opera_v2_new and in the China data (http://aeronet.gsfc.nasa.gov/cgi-bin/type_ from(Xia et those al., sites 2005; have Li beenever, et observations widely al., at used 2007; most Mi oferal et these sites al., have sites data 2007; were records Eck only longoptical et enough for al., properties to field-campaigns, 2010; characterize and (Zhu Bi seasonal only et variationsinadequate et sev- in al., for al., aerosol 2011). a How- 2013; comprehensive Fan2005). evaluation of et aerosol al., properties 2015). in Indeed, China (Eck the et existing al., data are for validating satellite retrievalsZhao et and al., numerical 2013a; Che models et of al., aerosols 2014; Lin (Xie et et al., 2014). al., 2011; monitoring aerosol optical properties,AERONET (Che and et it al., useswest 2009a). the CARSNET China includes same that 20 types(CMA) sites were of in located 2002 instruments first north for as and established60 dust north- stations aerosol by that monitoring. are the now Thisministrations, operated China network institutes, not and only has Meteorological universities by increased throughout CMA China. Administration to butresource This also for more has by studying become than local aerosol a meteorological optical national ad- properties over the di ing Dunhuang, Yinchuan, Beijing,lished Qingdao, from and 1997 Hefei in (Kimin northern et China, China al., and were a 2004).ferent estab- series At regions of in present, studies China SKYNETet has on has al., been optical expanded 2008, undertaken properties to 2014; forSun and Liu 10 that Hazemeter et radiative sites NETwork program al., (CSHNET) forcing (Kim includes 2009; over etsure 24 Wang dif- stations al., et aerosol established 2005; al., optical in 2014). Che 2004the properties Another to China. network, and mea- the Hand-held their Chinese sunphotometers2007). spatial AERONET/PHOTONS have and established been temporal four used2001, sites variations (Alfaro for in throughout et that Beijing al., program 2003; and Fan (Xin Yulin et beginning et al., in 2006; al., Che et al., 2009c), and there are now established in thefour 1990s. sites Zhang – Miyun, et Xinfeng, al. Waliguan, and (2002) Dangxiong. studied Several SKYNET aerosol sites optical includ- properties at properties. Accordingly, Qiu et al. (1998)trieve and AOD Qin based et on al. (2010) surface-basedobservation proposed broadband data. methods solar to Long-term radiation re- and measurementstrieved horizontal of in visibility China AODs from and 1960s2010). their to distributions 2000s (Qiu were and re- Yang, 2000; Luo et al., 2001; Qin et al., ibration procedures, calculation algorithms,has and made so it forth. di This lack of standardization 5 5 15 20 25 10 20 15 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | ected ff ected by ff 3000 ma.s.l.) and at > full field-of-view every E, 106.0 ma.s.l., which ◦ ◦ W, 2391.0 ma.s.l.) or the Mauna ◦ N, 116.32 ◦ N, 16.50 ◦ ected by dust aerosol particles with relatively erent types of Cimel instruments have been 12722 12721 ff ff W, 3397.0 ma.s.l.) global observatories which are the mas- ◦ ected by local sources and well above the surrounding ground ff N, 55.58 ◦ 1.5 % relative to the master measurements (Che et al., 2009c). According < 08:00) on clean and clear days were used, (b) the AODs at 500 nm on cali- + ered by 4.5 to 15.3 % compared with those measured by reference instruments. The requirements for inter-comparison calibration protocol for the CARSNET field Five CARSNET master quality sunphotometers were calibrated using the Langley ff to Brent et al.racy of (1998), the CARSNET yearly measurements, calibrations andstations therefore, were of the of AODs the high from quality the field and 50 instruments CARSNET reliable. ensured the accu- Loa, USA (19.54 bration days had totervals be between less the than measurements 0.20 madecalibrated had with and to two without be masters less major anddi than fluctuations, the 10 s. (c) instruments The the to AODs be time obtained from in- un-calibrated instruments fered by ter calibration sites for PHOTONS (alsoments RIMA) were and typically AERONET. These re-calibrated reference at instru-were Izaña then every installed 6 at months. the These Beijing-CAMS master site instruments (39.93 instruments were as(GMT follows: (a) only raw data collected from 2.00 to 6.00 a.m. After the calibration with the master instruments, however, the daily average AODs dif- is operated for both CARSNETall and field CARSNET AERONET), instruments and at theyprotocol least were once (Che used a et to year al., following inter-calibrate 2009a). the AERONET calibration method at the either the Izaña, Spain (28.31 940, and 1020 nm, (4)675, and 870, numerical 940, type at 10201020, nine and and wavelengths 1640 1640 of nm nm. 340, wereused Measurements 380, used to 440, at to 500, obtain 340, retrieve the 380,Dubovik AODs, total 440, and et precipitable measurements 500, al., water at 675, 2000a).et content 940 The 870, nm al., in total were 1999). centimeters uncertainty Aerosol (Brentdos in size et were the distributions, al., retrieved AODs refractive 1998; by indices, ismeasurements using and following about the single-scattering sky 0.01 procedures albe- radiance to described in 0.02 almucantar Dubovik (Eck measurements et al. and (2000b, direct 2006). sun 2 Site description, instruments, and data 2.1 Site descriptions As shown in Fig. 1ters and (Cimel described Electronique, in CE-318) detail were into installed the 2013. at Appendix The tables, 50 Cimel CARSNET stationsurban. sun sites can photome- The between be four 2002 classified remote stations into were three set general up groups: on remote, Tibet rural, Plateau and ( regional background site inpogenic northwest influences. China, The and twenty-fiveareas all rural these relatively sites sites una were are selected far to from be anthro- gions representative (eleven of sites), which aresmall mainly anthropogenic a influences, (b)not the only Loess by Plateau dust (fourral but sites, sites) also (c) which by central are more andanthropogenic anthropogenic a eastern activities activities and China than are (ten located the sites)ban near nearby which sites or desert (twenty-one are surrounded sites) more ru- by located strongly largemany in cities, a of the and which centers (d) are or ur- provincial heavily capitals. populated areas of2.2 cities, Instruments and calibration Cimel sun photometersmake were direct deployed spectral at solar each radiation CARSNET measurements site. in These a instruments 1.2 used; these include: (1) logicaland type 1020 at nm five and normalmal three wavelengths of polarization wavelengths 440, of bands 675, at 440,at 870, 870 940, 675, 870 nm, nm, 870, (2) (3) numerical 940, numerical type and type at 1020 at nm five eight and nor- wavelengths three of polarization 340, 380, bands 440, 500, 675, 870, surface. The rural sites can be further classified as sites representing (a) desert re- 15 min (Holben, 1998). Becausesites the to network has 50 been sites expanded at from the present, original several 20 di 5 5 10 20 25 15 15 25 10 20 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | cients ffi 3–5 % at ∼ 3000 ma.s.l. > ered from the orig- ff 20 % of the daily data. Finally, 0.60) mainly occurred in cen- ∼ > 3 % at visible wavelengths (440, 500, ± 0.20) occurred at remote stations, that is, erences of AOD in that comparison were ff < 12724 12723 erent geographical and optical conditions (Smirnov et al., ff 0.60; these include the urban site at Lanzhou and desert-margin > cients, and the cloud-screened AOD based on the method of Smirnov ffi The sphere calibration methods and protocols for CARSNET have been described Che et al. (2009) validated AODs from CARSNET-CAMS stations through com- were larger than 0.999 andalso had a were 99.9 compared % between significanceAERONET two level. Synchronous Zhejiang nearby observations Forest Yangtze University River site delta andbackground region the site other sites, (Pan the one Lin’an et at regional al., the CARSNET 2011). The di from north to southMt. (Fig. Waliguan, 2a). Shangri-La, and Low Lhasa AODs onand ( the Tibetan at Plateau Akedala at altitudes insubject a to remote only region of minimallow northwestern because anthropogenic of China. influences, this All and (Zhang of et the the al., aerosol 2012). remote loadings Large sites AODs are are ( very 3 Results: CARSNET measurements 3.1 Spatial distributions of aerosol optical3.1.1 properties in China Spatial distributions of AOD andThe Alpha spatial distribution offrom AOD (Fig. the 2a) CARSNET and stations Alpha (Fig. are 2b) shown based in on data Fig. obtained 2. In general, the AODs increased site at Hotan, Xinjiang Province. AODs from 0.20–0.40 occurred in semi-arid and arid the AODs calculated byASTPWin ASTPWin AOD procedure values vs. were AERONETAERONET about results, at showed 0.03, 1020, that 870, 0.01, 670, the 0.01,two and and networks 440 nm, 0.01 were respectively. larger Thus, very the than sets consistent those of from with results from one another as the correlation coe less than 0.02, which againand indicates AERONET. similar accuracies in the results from CARSNET tral and eastern China,northeastern especially regions plain, with north strong Chinabasin, anthropogenic plain, and influences Yangtze Guanzhong in River plain the delta, (Zhangalso Pearl et showed River al., AOD delta, 2012). Sichuan Several sites in northwestern China by Tao et al. (2014). The CARSNET sphere calibration results di inal values provided by the manufacturer, Cimel Electronique, S.A.S., by infrared wavelengths (1020 and 870 nm) and and 675 nm). Similar toinstruments were Brent done et annually to al.ments. ensure (1998), the sphere accuracy of calibrations the of sky all irradiance measure- CARSNET field 2.3 Data processing and quality control The AODs wereturer calculated of using the thewithout sunphotometers. ASTPwin This cloud-screening), software software Level providedof can 1.5 by AOD Smirnov provide the (cloud-screened et Level manufac- For al., AOD 1.0 AOD 2000) the based (raw and present on results calibration Angstrom study, the coe Exponents all work (Alpha) AODet between al. data 440 (2000) were to alsobeen were 870 computed nm. completely obtained. by We validated note although interpolationtal that the data the of procedure cloud-screening obtained tested the technique under favorably has inter- using di not experimen- ing the MODIShttp://modis-atmos.gsfc.nasa.gov/IMAGES/. Level-1B Daily average granule AODs (MOD02_1km) werecomputed, the and images, first any cases values which where measurementswere are were eliminated. made This available less processing than procedure from 10 eliminated times in a day 2000). To further ensureby-site, and the any data unreasonablelarge quality, data all AOD points were the were deleted. data caused For were by example, checked the some manually clouds, exceptionally site- and this was determined after check- parisons with data from the AERONET stations in Beijing. A comparison between the monthly and yearlywere averages the of Angstrom the exponents AODs between were 440 calculated and at 870 nm. each wavelength as 5 5 15 25 10 20 10 15 20 25 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 0.80). > 0.40 from < 0.60 in spring and > 0.40 at the sites near < 0.29. These results are ± 0.60 in spring and summer < 0.20, in fall (6 sites) and winter < 1.20. These results reflect the trans- 0.60 were located in northern China. > 1.20) were found along the southern < > 0.80) than those of central and eastern re- < 0.60 were found in central and eastern China 12726 12725 0.04. The Angstrom exponent varied from 0.59 > ± 0.40 occurred only at one site, Kunming, and then only in < 0.60–0.80 in arid regions of northern China. In particular, the 0.40 in the Taklimakan desert region (e.g., Tazhong and Hotan) ∼ < 1.20 all year, and this reflects the dominance of fine mode particles > 0.80 were found in central and east China from summer to winter and 0.60 in fall and winter, and this pattern can be explained by the frequent > < 0.14 from September 2009 to August 2010, and this is similar to the long- ∼ 0.60 in spring, summer, fall, and winter season, respectively, and almost all < In spring, there were many sites with Alpha 0.80–1.00 in central China and 1.00– The spatial distributions of Alpha for the four seasons are presented in Fig. 3f–i. From Fig. 2b, we can see that the spatial distribution of Alpha in China also shows Figure 3 shows the spatial distributions of AOD and Alpha separately for each of the spring to fall andaerosols 0.40–0.60 throughout in the year, winter, withwinter and (Che greater this et impacts al., implies of 2013). the fine-particle Fornyu, southern presence pollution Alpha China, sources was of including the in coarse stations at mode Nanning and Pa- 1.20 in the Yangtzein River the delta other region, seasons when and they these were values typically were obviously lower than of these sites areparticles located transported in from northChina. semi-arid Alpha China. and This arid reflectsin regions the south of China presence northwestern all ofthe year and coarse fine around, mode. northern dust suggesting that the particle size distributions favored port of large dust(Chen et particles al., from 2009). As northwest for China the Taklimakan to desert eastern region itself, China Alphas were during the spring Eck et al. (2005) suggestedwhen that Alpha coarse was mode less aerosols thanAlpha were 0.80. relatively In more this abundant study, there were 24, 10, 14, and 15 sites with generally representative of the aerosolinterior optical of properties Asia. at background Cheaveraged regions et in the al. (2011) reported that the AOD at 500 nm at Mt. Waliguan the boundary betweenThere China also and were Mongolia, more and(9 sites sites) this with compared was with low spring true AODs, (2 that throughout sites) is and the summer year. (3 sites). From Fig. 4a andLhasa, b, Mt. one Waliguan, and can0.18, with Shangri-La. see an Indeed, arithmetic small mean the AODsat of AODs at 0.14 Mt. at the Waliguan these to four sites 1.29 remote were at sites 0.11– Shangri-La of and Akedala, averaged 0.97 dust storms in spring and2003; summer Eck and fewer et dust al., events 2005). in fall It and was winter also (Gong found et that al., the AODs were caused by the chronic anthropogenic emissions in the region3.1.2 (Tan et al., 2009). Aerosol optical properties in remote, rural, and urban regions of China fall and winter. Monthly average AODs summer but clear variability, for example large Alpha ( regions of north China andground some regional site background for sites the suchnortheast as north Mt. China China Tai plain. – plain the back- and Mt. Longfeng – the background site onreaches of the the Yangtze River andthe at aerosol particles clean sites in of thesethe northeastern areas desert are China; regions smaller this of than shows northwesternthe in that Alpha most China values other and were regions considerably industrial lower ofgions region ( China. such of In as northeastern North China, China Plain, Guanzhong Plain and Sichuan Basin (Alpha compared with 32 in the fallextinctions and of 30 China in were winter generally (Fig. larger 3a–d),winter. and in Moreover, this spring most shows and that of summer the compared the aerosol In with sites southern fall and with China, AODs AODs all year around. The AODs in the Taklimakan desert region were four seasons. Of the 50 CARSNET sites, 27 had AODs Alphas were typically which suggests that large mineral dustpopulations particles in were this major region components (Che of et the al., aerosol 2013). The Alpha values were 5 5 10 25 25 15 20 20 15 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 0.19, ± 1.00 and 0.20) from > > 0.23. The large 0.28) and Hotan ± ± 0.19 for Alpha, were ± 0.53 ects of dust particles on = ected by springtime dust ff ff 0.06 at 440 nm and Angstrom expo- 0.92 respectively. The average AODs ± ∼ ect the aerosol populations of the CLP. 0.12, respectively. The AODs also varied ff 0.14 ± = 0.12 for AOD and 0.55 12727 12728 ± 0.35 and ∼ 0.40 except for Tazhong (AOD 0.18 and 1.19 < ± 0.05. These values are consistent with the results reported by ± 1.00 indicates the aerosol populations were predominantly com- > 0.12. Although some stations, such as Ejina, Jiuquan, Dunhuang, and 0.22). These two stations are located in Taklimakan desert region, one ± 0.21 from March 2009–April 2012). ± ± 0.61 0.59 0.18 while Alpha ranged from 0.52–1.50 and averaged 1.05 0.05 and 0.82 = = ± ± The AODs for the urban CARSNET sites showed a range 0.4–1.00 with an average Figure 5 shows the seasonal variations in AOD (a–d) and Alpha (e–h) at the The AODs for eleven rural stations in desert regions varied from 0.23 to 0.61 and The AODs at ten rural sites in central and eastern China show obviously higher AODs The four rural stations located on the Chinese Loess Plateau (CLP) showed ranges 0.74 China are strongly influencedpopulations by anthropogenic are emissions relatively because small, eventhe the though sites sites their at are Shangdianzi downwindnear and of Shanghai Gucheng (Che mega-cities. are et For near al., example, Beijing 2009b). while Dongtan and Lin’an are AODs in spring andbined summer AODs were in factors fall of andthe 1.57, winter Alphas 1.62, at in 1.29, remote, fall rural, 1.18, andand and and winter summer urban 1.14 were seasons. sites, to factors respectively. These com- of However, comparisons 1.27, show 1.28, that 1.11, 1.10, the and e 1.09 to spring CARSNET remote, rural, and urbantypes sites. In of general, sites the AODs in were lower fall at and all three winter compared with spring and summer. The combined AOD and Alpha portation, building construction, andaerosol in burning metropolitan garbage areas of are China. a major component of the posed of fine modethan particles. that However, of the rural averagefugitive sites dust. Alpha Chen at for et eastern urban al. (2010), China, sites for and was instance, pointed this lower out is that probably fugitive dusts due from to trans- the presence of AOD and Alpha werewith more the rural apparent and at urban the sites. remote and3.2 rural desert Temporal sites variations compared in AOD and3.2.1 Alpha Monthly average AODs and variationsThe in Alpha AODs at at remote Akedala sites in northwest China showed high monthly means ( averaged 0.34 nent Minqin, near desert regions are known to be frequently a (AOD and reported AODs and Alphas of higher than those overthe the Loess desert Plateau regions. were greater Thisrelatively compared shows more with that the fine the desert particles. aerosolsites regions The are loadings and larger numbers that over there than of were aerosols those persons likely at living occurred the over in desert thethropogenic and stations, CLP. In emissions and around fact, as and earlier the a dust studies CLP (Alfaro result have storms et shown more do al., that anthropogenic 2003; a both Che an- et al., 2009c). compared with stations located nearfor the the deserts rural sites or were CLP. Theover 0.54 a average large AOD range, and from Alpha 0.26varied to from 0.78, 1.2 and to the 1.38, Alphas suggesting at all a these dominance sites of were fine particles. The sites in eastern February to April, and thisdust was from presumably the a nearby Gobi, consequenceKazakhstan. sandy of The lands, the AODs and transport were deserts lower of as from mineral August well to as October the when deserts there in was eastern more pre- of the world’s largest sources forAlphas desert over dust the (Zhang rural et desert al., 1997; stations Che varied et from al., 0.22–0.80 2013). and The averaged 0.55 Bi et al. (2011) who studied aerosol optical properties at SACOL rural site on the CLP term measurements reported here (AOD storms, the average AODsat were most not of as these large sites as were one might expect. In fact, the AODs and these values reflect the light extinction properties ofin coarse dust the particles. AODs0.42 and Alphas of 0.37–0.46 and 0.79–0.89, respectively, andand means Alphas of at the CLP stations, 0.34 5 5 15 10 20 20 25 15 25 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 0.40 0.09, 0.43, 0.68, 0.09, 0.10. 0.06) ± ± 0.20 in 0.18 in ± ± ± ± < ± > 0.12) were 0.10 in fall ± < 0.38 in July at erences in the ff ± 0.08, 0.20 0.30, 0.49 ± ± 0.09 and 0.16 0.10 during March to ± > 0.39, 0.39 ected by mineral aerosol from ff ± 0.41 at Dunhuang, and 0.55 ± 0.05) and Zhangbei (0.18 0.16 at Tazhong. The four rural sites ± ± ected by springtime dust events. In sum- ff 12730 12729 0.27 at Minqin, 0.55 ± 0.03, respectively. The AODs at Shangri-La in southwestern ± 0.12, respectively. These low springtime Alphas suggest that ± 0.35 in August at Lahsa. At Shangri-La and Akedala, the Alphas 0.12 at Hotan and 0.22 ± ± 0.05 and 0.11 0.30 at Ejina, 0.48 ± ± 0.40 from February to October. The monthly-averaged AODs were the lowest 0.80 throughout the year, and therefore, fine mode particles were relatively 0.14, and 0.53 0.04 in November at Ejina, Dunhuang, Jiuquan, respectively, and 0.26 0.26 at Wulate, Xilinhot, Zhurihe, and Zhangbei, respectively. Minima in the AODs > > ± ± ± The AODs in spring and summer were high and low in fall and winter at Lhasa and In general, the monthly average Alphas at Akedala and Shangri-La and were larger The four rural sites in the interior of Inner Mongolia showed generally similar vari- deserts in western Chinaaverages for and Alpha at local Akedala, Mt. dustseasons: Waliguan the and uplifted Lhasa minima from were at lower these Tibetan in three spring Plateau. sites than occurred The other in monthly March, with values of 0.90 and winter. The AODs reportedby here for Cong Lhasa et are slightlystrengths al. and larger numbers (2009), than of those dust and storms inactivities. as this a The well study as could CARSNET local Lhasa contributions be fromof site anthropogenic caused is AERONET by located is in year-to-year 125anthropogenic the km di activities city north (Cong itself, to et whilewere Nam al., Lhasa slightly Co 2009). city, larger station The where than AODswere there at 0.11 those are Mt. at Waliguan no Shangri-La (0.14 China impacts or also Lhasa from showed two where local seasonal peaks; theMay that and mean is, again the AOD from AODs values were JulyThese to small September AODs while at in Shangri-Lain other this also periods, region show the are that very AODs even were low the compared maximum with aerosol other loadings than regions those in that China. at Mt.tend Waliguan and to Lhasa, be and smaller this atis indicates the that located latter the on two aerosol sites. the particles to This northwestern is the margin likely transport of due to Qinghai-Tibet ofet the plateau dust al., fact and from that 2011; therefore Mt. desert Gong subject Waliguan et regions al., in 2003). western Lhasa China also and can middle be Asia a (Che Waliguan and 1.22 respectively, while the minima at Zhurihein (0.11 January. The low AODs in winter and autumn occurred when the ground surface were abundant at these two sites. 3.2.2 Variations in monthly AODs andMost Alphas of at the the rural eleven desert ruralin sites CARSNET spring sites and near summer thethe and aerosol desert low populations regions at AODs showed these in largemer, sites autumn the AODs were impacts and a from winter, dust and eventstral weakened this and while is anthropogenic western emissions evidence fromgions that China cen- (Che evidently et contributed al.,temperatures to restrict 2009c). the convection In aerosol even autumnwinds. loadings though Hotan and over incursions and winter, these of Tazhong, dustAOD the re- cold storms two air rural are can sites rarein bring located because November, strong in 0.31 low Taklimakan desert,in showed desert regions ofwere northwestern 0.39 China each showed maximum AODs in April; these occurred in November at Ulate and Xilinhot with averages of 0.19 at Juquan. The minima occurred in fall or winter, with values of 0.14 0.45 0.25 coarse particles from dustfall, events the were prevalent Alphas at were these larger three than sites. In in summer spring, and with a maximum of 0.96 January at Minqin. ations in the AODs; that is, maxima in June of 0.44 0.17 Mt. Waliguan, which are bothtwo on sites the Tibetan exceeded Plateau. 0.15 Monthly in average AODs spring at and these 0.10 in summer, and they were June and July, and thisin eastern can Europe, be western attributed Russia,et to and al., eastern the Kazakhstan, 2008). transport which The of area AODs all pollutants result increased upwind from of from (Qu the countries October local to burning December, of and coal that for was cooking and probably heating. cipitation in the region and the winds were weaker. The AOD at Akedala was 5 5 15 10 25 10 15 20 25 20 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | < erent ff 0.80 in March < 0.3, which is lower ∼ 0.80) all year; and this < 0.40 in spring and summer, and the > 0.85) in August. This is another indication ∼ ected both by dust events and anthropogenic ff 0.35 during April to June, and the springtime 12732 12731 > 0.44) occurred in June; and that was probably caused by the ± 0.48) greater than at the three sites just discussed, indicating 0.30 in November and December. At Mt. Gaolan the AODs in ∼ < ected these sites more than the others. In December and January, ff 0.20) for more than six months (February to October), and therefore large < 0.30 from January to September. The seasonal variability in the aerosol at Yulin central and eastern China Loess Plateau > In June, the AODs for the North China Plain and Yangtze River delta station (Shang- The AODs at Huimin, Gucheng and Yushe in the North China Plain ranged from Monthly average Alphas at most of the rural desert sites, including Ejina, Zhangbei, The Alphas for the four sites on the CLP showed obvious seasonality, with Alpha The monthly average AODs at the four sites on the Loess Plateau showed di dust particles a the Alphas at most ofother the types CARSNET of rural sites, desert andbiomass sites this burning were was as higher likely both due compared used to with extensively presence the for domestic of heating fine3.2.3 (Eck particles et from al., coal 2005). Variations and in monthly average AODs and Alphas at the rural sites on the and April when dust events wereAlphas common. ( The two sites in the Taklimakan showed low temporal trends. At Dongsheng,monthly the maximum AOD (0.71 was was likely caused by a mixture2003). of dust and local anthropogenic emissions (Alfaro et al., 0.70 from March to May but higher values ( hygroscopic growth of particles in(Eck combination et with al., gas-particle conversion 2005).October, processes At and Yan’an, it the was AODspring varied and smoothly winter around werewere 0.35 higher from than January in to summer and autumn while at Yulin, the AODs that aerosol particles at these sites are a activities (Fig. 11). dianzi, Mt. Tai, Gucheng, Huimin,sult Lin’an, of Dontan) were the quite burninga high, of site most the surrounded likely as straw bythe a farmlands, (Logan two re- were et following higher months; al., in and 2013).agricultural this September fields Indeed, is than in likely the in September. because Similarly, AODs the peasantsOctober, the at prior and typically AODs at Gucheng, burn month this Tongyu straw or also were from aslands. may high have as been 0.34 due in to the burning of biomass in nearby farm- The rural CARSNET sites in central(1) and Tongyu and eastern Mt. China Longfeng can located be inHuimin, divided northeastern Yushe into and China, three Mt. (2) groups Tai in Shangdianzi, the Gucheng, tan North China in Plain; the and (3) middle Changde,and and Lin’an, and Tongyu lower Dong- in reaches northeast of China the and Yangtze River. Mt. The Tai AODs in at north Mt. China Longfeng were 3.2.4 Variations in the monthly average AODs and Alphas at rural sites in Lin’an, the sites in0.78, the and Yangtze River these region were ofin higher southern northeastern than China, in China the the showed AODsvalues North were were AODs China obviously 0.59– higher Plain. compared Mt. with Longfeng the and other Tongyu months. 0.58–0.71 as a result of theChina heavy is pollution aerosol industrially loadings there. developed,June This and and region from of biomass north September burning to is October also (Eck et common, al., especially 2010). in For Dongtan, Changde, and compared with the ruralShangdianzi stations – in the central and backgroundwas eastern site a China for factor (Fig. the of 12). Beijing–Tianjin–Hebeihigher The 1.6 (Jing–Jin–Ji) aerosol AODs loadings ( region at in this region. indicates the coarsesites particles (Zhurihe, were Hami, the Xilinhot, dominant Wulate, and aerosol Minqin), components. the As Alphas for were other Jiuquan, Dunhuang, Tazhong and Hotan, showed low values ( was often frozen or coveredwindblown by dust. snow – conditions that would prevent the production of 5 5 25 20 15 10 10 15 25 20 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 0.16). 0.80 at ± 0.48 and < 0.70 from ± > 0.43). The seasonal pat- ± 0.32 in June, and the minimum ects of the dust storms in spring 0.45 from September to October 0.30) and August (0.64 ± 0.70 only in July and November– ff < ± < 0.60 in the other months, and this is consistent 12734 12733 0.30. The low AODs in the warmer months were < < 0.65) from December to February compared with > 0.32) and also in August (1.17 ± 0.60, in March (0.67 0.90 throughout the year. Three of these sites have monthly > > erent from the rural sites in other regions of China, including ff 0.40 from October to December, probably due to the influx of < 0.80 from summer through winter, but in spring they are > ects of coal combustion at Urumqi can be seen in the seasonality in the ff 0.34) was in July. At Dontan, the AODs were 0.42) and March (1.02 0.80 in Feburary and August. ± ± ∼ erent from the trends at the other two urban sites, Yinchuan and Xi’an. This is be- erent from the rural sites of northern China. The AOD of Changde was Of the five urban CARSNET sites located in north China, Beijing, Tianjin and The AODs at Yinchuan varied smoothly between 0.40–0.70 with high monthly- Shangdianzi and Mt. Tai showed similar monthly variations in AODs: they increased From June to September, which is the biomass burning season at the rural sites In general, the Alphas at the rural sites in central and eastern China were relatively ff ff December; the maximum monthly average was 0.96 Yushe (March and April), Changdeclude (April), that and fine Mt. mode Tai particleseastern (April were China, and and relatively that May). abundant was Thus, at mostbustion, we likely the biomass due con- rural burning, to gas-particle sites anthropogenic conversion). emissions in The (e.g.particles central high coal and relative was com- abundance notably of di fine the nearby desert and CLP sites, where there wereof more coarse-mode Tongyu, particles. Shangdianzi, Mt. Tai, Gucheng, Huimin, Lin’an, and Dongtan, the Alpha average Alphas as well; thisgases reflects to the particles over hygroscopic awere growth broad area greater of (Eck than et fine al., 0.50 particles 2005). with At and Beijing respective and the maximum Tianjin the monthly conversion AODs means of of 1.10 Zhengzhou showed high AODs throughoutto the year August around, were and high a AODs common from June characteristic at the other two sites (Dalian and Datong) values were clearly larger thanin those in October May. at Alpha also severaltoo, was other is higher sites, more in including September than than Shangzianzi likely related Huimin, to and the Yushe, emissions3.2.5 and of this, fine PM Variations from in biomass the burning. monthly averageOf AODs the and four Alphas urban at sites theseasonal in urban trends; northwestern stations that China, Urumqi is,di and high Lanzhou AODs showed the in same winter and low values in summer, and this is AODs – they were much higher ( terns at Yinchuan and Xi’anand presumably the reflect hygroscopic the growth e ofhumidity (Su particles et in al., August 2014). due to the summertime increase in cause large quantities ofwinter, coal and are that burned is for2009). a heating The e major in both source Urumqi of and PM Lanzhou at in those sites (Li et al., 2005; Quan et al., June to September, when they were Xi’an was similar to(1.07 Yinchuan and showed high monthly-averaged AODs in February averaged AODs, that is not only due to thetation smaller and amount stronger of convection coal insites burned the (Liu but warmer also et months because al., reduced increased 2004). the precipi- PM loadings at both cold air in fall andat winter which Lin’an, flushes polluted Dongtan, airdi and from region. Changde, The in monthly variations middle and lower Yangtze River region, were from January (0.20–0.30) to June(0.20–0.30). (0.60–0.70) Gucheng and then and decreasedmonthly Huimin through average December are AOD were located notare as near fewer obvious farmlands, local as anthropogeinic at and activites Shangdianzithe the and (Hänel temporal Mt. et changes variations Tai al., where in were 2012).AOD there similar Nevertheless, at in for Yushe general, was the four sites on the North China Plan. The January–March and in September but with what has been reportedRiver for (Gong other et urban areas al., in 2014). the The middle AOD section at of Lin’an the Yangtze was low from March toof May coarse compared particles. with AlphaLin’an, other and at Dongtan months, was Tongyu, and Mt. that Longfeng, reflects Shangdianzi, the Gucheng, influence Huimin, (0.58 and 5 5 25 10 20 15 10 25 20 15 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 1.00 0.40 ± > 0.12 and ± 1.00 in February > 0.50 throughout the 0.60, and these high 0.80) at the two sites > > > 1.20 for both sites. This could be 0.50 at all four of these sites, indi- ∼ 0.15 in autumn and 0.72 ≥ 0.30) from October to February, which ± < 0.12. This indicates that the particle loadings 0.46 during spring and summer. In February, 12735 12736 ± ± 0.40) at Kunming were found from March to Septem- > 0.60 at Shenyang, Anshan, and Benxi from April to August, > 1.00 from December to April, with a maximum monthly mean of 1.30 ered from each other. The AODs at Chengdu were > ff 0.57 in June. At Zhengzhou the monthly average AODs were ± Panyu and Nanning, two urban sites in southern China, show temporal patterns dif- Four urban CARSNET sites, Shenyang, Anshan, Benxi, and Fushun, are located in Dalian, a coastal city on the Liaodong Peninsula, has experienced rapid economic The variations in AODs at Chengdu and Kunming, two urban sites in southwestern There are four urban CARSNET sites (Hefei, Nanjing, Pudong, Hangzhou) in the 0.70 during September to January. These low values are more than likely because cating a regional veil of pollution,tions and made this by result Wang et is al. in (2012) agreement and with Xiao previous et observa- al. (2011). Monthly average AODs ferent from the Yangtze River delta sites. AODs were high ( values were likely caused by2013b). the combustion of coal for domestic heating (Zhao etYangtze River al., delta region, whichall is of one China. of Monthly the mean most AODs economically were developed generally areas in were observed from June tothan August, the and these minimum values monthly arethose about AODs. in a Furthermore, May factor at the of eachburning two AODs of higher of the in four agricultural June sites, crop werelower and residues higher the than high (Cheng than that loadings et at were∼ al., Hefei, likely caused Nanjing, 2014). by or The the Pudong Hangzhou: AOD is the at located monthly Pudong near the means was the coast, East at and Sea Pudong polluted (Pan air were et can al., be 2010). replaced by cleaner air from and this reflects the heavywith aerosol the loadings findings in of this Xia region. etcenter These al. of results (2007) are who Liaoning consistent reported Province thatthe was the AODs average we 0.63 AOD measured (500 nm) at in Shenyang, the Anshan, and Benxi were northeastern China, a heavilyas industrialized high region, as and those the at AODsnortheastern the at urban sites these sites were sites in high were The north AODs in China. were We spring typically also and found that summer, the especially AODs from at the June to August. in Dalian are less thanthe in influx the of Chinese relatively mega-cities, cleanis and maritime an one air important likely at harbor, contributing and the factorthe therefore coastal is aerosol emissions site. loadings from On at shipping the thisspring, also site other and could (Zhang hand, like contribute et Dalian many to al., ofin 2015). the spring. The rural AODs sites at above, Dalian this were is high probably in due to the influx of dust during two periods, firstand from during March both to April ofmidity and these (Andreae second et periods, from al., biomass0.46–0.66, September 2008; burning in to Tan et is June October, al., frequent and 2009).maximum July with Interestingly, AODs, at high the which both AODs relative were sites, were hu- found and low, in these from March were with roughly half of the monthly year and 1.00 China, di development in recent decades. The AODsto at those Dalian showed at monthly Beijing variations and similar tially Tianjin, lower, but with the magnitude an of annual the mean AODs 0.54 at Dalian were substan- and from June tobations August. to These the very atmosphere. highin The AODs Jing–Jin–Ji combined reflected region AODs the of forwinter. anthropogenic north Beijing pertur- China, and were Tianjin, 0.74 both located due to relative abundance ofremoval rain of in PM the by late wet spring deposition and as early well summer as and changes the in resulting emissions (Tan et al., 2009). in March. Clearly, the aerosol loadingstent at with Chengdu previous were measurements. very Indeed, heavy,have and been high this attributed aerosol is to consis- loadings unremitting intrapping anthropogenic the emissions of Sichuan coupled pollutants with Basin in the thecomparison, physical basin the (Luo AODs at et Kunming al., were 2001; low Li ( et al., 2003; Liu et al., 2014). In is the dry season. Highber, AODs which ( are in the wet season when the hygroscopic growth of the particles would 5 5 25 10 20 10 15 15 20 25 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | c ffi 0.80 during this > ect on the northern urban ff ects of seasonal biomass burning. ered from October to April, and this ff ff 1.00, indicating that fine mode aerosols ected the Alphas at some of the urban ff > 12738 12737 ects of biomass burning on the Alpha values for the urban CARSNET sites ff 0.80 from March to April, but again there were some variations among sites. In < The AODs and Alphas at the urban Lanzhou site were both higher than at the rural These coarse particles include not only natural dust transported from the deserts in Except for Nanning and Kunming in southern China, almost all of the urban sites The e and a boomfields in for building the construction plantingand (Fan of this et crops material al., also canAugust, cause 2009). be a the transported great Preparations majority emission to of of urban of agricultural the areas mineral Alphas (Mei aerosol were et in al., spring, 2004). From June to were dominant at thisby time gas-particle of conversion reactions, year. and Many numerousvolatile of studies organic which these compounds have are fine shown that converted particlesas the into a were secondary result likely organic of produced aerosols conditionshigh in favorable for humidity summer photochemical in reactions summer (Shao2010), et also al., and leads 2009). to these The the processes hydroscopic undoubtedly growth a of fine PM (Eck et al., CARSNET sites. are not as apparent assome at of the urban rural sites, sites includingthe in Beijing, Alphas central Hefei, were and Nanjing, high eastern Pudong, in China. Hangzhou, June Nevertheless, and and at Panyu, from September to October, and this may be related at Mt. Gaolan from April to September, but they di site at Mt. Gaolan– (Figs. this 14 was and true 10), throughout which the is year. about The 600 m AODs higher at than Lazhou the varied urban in site the same way as to the emissions of finesources particles in from biomass these burning. urban However,needed because sites to the are investigate aerosol this complex possibility. and not well understood,3.3 more studies are Comparisons of urban stations withRapid rural urbanization stations in parts ofety China of has problems, perturbed including the visibility atmosphereCARSNET impairment and operates and caused air two a pollution, vari- pairs etc.Figs. of (Che 12 et sites and al., with 2007). 14,paired both one rural urban site can sites Shangdianzi see and showedAOD that very rural at both consistent Shangdianzi stations. temporal was the From variations of AODsjing although course, was and much the lower lower the than than Alphas that thatwere Shangdianzi, at at larger which than Beijing. Beijing shows those The and that at Alpha the theof it’s at rural particles Bei- fugitive site. in This dusts the can urban in beparticles explained area the during by the transport urban greater to production regionsurfaces the all (Fan cause rural et the site. emission al., Transportation, of(Chen construction fugitive 2009) et dust activities, al., and particles 2010). bare in the On Beijing theetated, settling and other and other hand, out this large the cities tends of surfaces Shangdianzi to larger are suppress more the heavily production veg- of PM in the area. decoupling probably results fromto changes September, in the the boundarysimilar surface variations layer in boundary at the layer. both aerosolhowever, From convection sites populations tends April at is to the be normally weak twoat and deep, sites. the Mt. From and boundary September Gaolan. layer this to atboundary promotes The April, Lanzhou is layer, aerosol lower and than particles thatSeptember are is to then April. why mainly the concentrated AODs in at the the shallower two sites become uncoupled from north and northwest Chinadust but have been also produced fugitive in dusts. some urban Indeed, areas large as quantities a result of of fugitive increased vehicular tra sites than the southern ones. period even though they were lowercoarse than particles, in especially other months. mineral This dust, pattern have is a evidence that greater e showed lower Angstrom exponentsbut from the March patterns varied to somewhat May amongnorth, sites compared (Fig. and with 15). northeast At other the China urban periods, were (except sites in for northwest, Dalian andcontrast, Tianjin – the two Alphas coastal for sites), the Alphas sites in southern China were generally be expected. The AODs at bothcompared Chengdu with and other Kunming periods, were probably high due in to March the and August e 5 5 20 10 15 25 10 15 20 25 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 0.08, + 1.00 at Mt. Gaolan. The < 0.03 from 2009 to 2013, and this ∼ 1.00 and > erence in particle size can be explained ff 12740 12739 1.00 (Wang et al., 2010). > ect the ambient aerosol. ff While strong winds can dissipate anthropogenic aerosols in eastern China region, Increasing aerosol emissions obviously would tend to increase the AODs over most The composited average AODs for these twelve sites was highest in 2003, and there In contrast to the AODs, the Alpha values varied coherently at Lanzhou and 3.4 Long-term variations of AODs overThe China variations in annualfor AODs the for entire the twelve studyinclude CARSNET period, five sites that urban that isdesert were sites sites from in (Urumqi, (Tazhong, operation 2002 Ejina, Lanzhou, Dunhuang, tosites and Beijing, (Mt. 2013, Xilinhot), Longfeng, Tianjin, Shangdianzi, are and and three and showna Lin’an), regional Datong), and in reasonable background as representation Fig. four a of group, 16. rural Fig. they how These can 16, conditions be most considered have ofthe changed one these in exception sites China. was showed Tazhong, Asdecrease which overall shown was is decreases not in in in continuous, theat however central AODs as some of from the the sites, 2006 AODs Taklimakan including Desert. apparentlyShangdianzi. to Urumqi, The increased Ejina, 2011; from Dunhuang, 2012 Tianjin, Beijing, Mt. Longfeng, and was a slight decrease(Fig. from 17a). 2006 From to Fig. 2009we 17b, followed can which by see shows an that the increaseaverage. AODs departure Moreover, from in of the 2009 2003, composite the to 2006, AOD AODs 2013 and increased from 2012 the were average, 0.03–0.08 larger than the 12 yr by types of sourcestle for vegetative the cover, PM. and Mt.sources. large Gaolan In is dust Lanzhou, located there particlescles, on is and can the the an production be CLP abundance of raised whereAlphas secondary of aerosol there from anthropogenic particles is local sources also lit- contributes for and to fine fine regional PM parti- and they also can transport mineralChina. dust Figure from 16 desert regions showsin in that northwest northern the and and rural northwestern north desertmay China sites be had such larger related as AODs toHowever, in Ejina, much the 2006 Dunhuang, of stronger compared Xilinhot the winds with precedingobservations 2007, and discussion will and hence be is this needed greater still to production speculative, test and of these more ideas dust studies in in the and 2006. future. et al., 2010; Fu etthropogenic al., emissions 2011), in and both thestudies of near-surface have these air shown changes sampled that would for favor amay the CARSNET. have weakening buildup Indeed, led of of recent to the an- monsoonal an2011; circulation increase Chin, in in 2012; recent aerosol Zhua decades loadings over et “weak” many al., year parts 2012).CARSNET in of sites As China terms for (Liu an of that et exampleand al., the year this of could showed Asian this, reflect a the monsoon. 2003also departure weakness a was The of from the regarded composite the monsoon, as and AOD average therefore, of for changes about in the climate twelve of China, but anotherical possible environment, reason especially for the theloads trends intensity over in of China AODs the are is Eastciated strongly changes Asian precipitation influenced in (Yoon monsoon. et by the In al., the phys- of fact, 2010). Asian windy aerosol There monsoonal days is and flow also the and some wind the evidence speeds that asso- in the China numbers have decreased in recent decades (Jiang suggests that aerosol loadings in Chinathe may reasons have increased for in any recent increase years.and in Identifying one aerosol obvious loading possibility would is be that2001; that critically Lei has important et been al., of an 2011). course, increase in emissions (Street et al., Mt. Gaolan (Figs. 15 and 11),tion and dependent. this That is likely is, because thethe this aerosol parameter year size is even variations not though concentra- at the both Alpha sites at are Lanzhou similar was throughout Alpha values show thatwere while even the smaller particles at were Lanzhou, mainly and fine mode this at di both sites, they 5 5 25 20 15 10 15 20 25 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | ± 0.03 0.04 ± ∼ 0.18 while the 0.60 in spring, ± < 0.80) compared with 0.20) were found only < ected by the burning of < ff erent patterns at the remote, rural and ff 12742 12741 0.80 also occurred in central and east China region > 0.05. The AODs at rural sites in central and eastern China ± 0.12. The AODs at this region varied over a large range, from ected by both natural and anthropogenic mineral dust from ± ff ected by changes in the strength of the East Asian monsoon as ff 0.12). The AODs and Alphas at the rural stations on the Loess ± 1.20), which are caused by large proportions of fine particles, were 0.18, and the range for the Alphas was 0.52–1.50 with average 1.05 > 0.60) mainly occurred in central and eastern China where heavy in- ± > 0.05 and 0.82 ± 0.29. In comparison, the AODs at rural desert stations varied from 0.23 to ± The annual variations in the AODs at the 12 CARSNET long-term (2002 to 2013) A comparison of AODs and Alphas between pairs of urban and rural stations in Monthly-averaged AODs and Alphas show di The monthly average AODs at the urban stations ranged from 0.40 to 1.00 with an For most sites in north China, the aerosol columnar extinctions were larger in spring Large Alphas ( The AODs at the remote sites ranged from 0.11 to 0.18, and averaged 0.14 observation sites show a decreasing trendfrom from 2009 2006 to 2013. to This 2009 suggests butreversed the an a possibility increase decreasing that of the trend aerosol andvariability loadings increased in in AODs China in is have recent a years. However, the year-to-year Beijing and Lanzhou showed thataerosol cause seasonal changes variations significant in in the thedata aerosol vertical optical for properties. the distribution A Lanzhou–Mt. of comparison Gaolan the ofwas paired the an sites important indicated determinant that of the the depth seasonal of variations the of boundary PM with height. coal for heating, especially in north China. urban sites, and thisThe most reflects important the factors driving spatialare the the temporal and variations natural temporal in dust aerosol heterogeneityoptical events optical and of properties properties anthropogenic the are activites. aerosol. March a In to eastern May, China, and the burningcontribute aeosol to of the biomass high and AODsThe the from aerosol formation June optical of through properties October second in at aerosol winter most particles season rural are and strongly urban a sites. average Alpha was 1.19 0.23; these large Alphas indicateAODs that the were aerosols lower were in predominatelyspring fine remote, mode. and rural, The summer. andspring However, urban and the sites summer Alphas seasons. in in fall fall and and winter winter compared were with larger than in the 0.26 to 0.78, and1.02 the to Alphas 1.38, at and suggesting all the of dominance these of sites fineaverage were particles. of larger 0.74 than 1.00, ranging from on the CLP. The average AOD at rural sites of East China was 0.54 and summer than in fall and winter. About half of the sites had Alpha those in the centralPlain, and or eastern Sichuan regions, Basin. such as the North China Plain, Guanzhong 4 Summary and conclusions In this study, data collectedto from the characterize CARSNET the network aerosol fromgenerally 2002 optical increased to from properties 2013 north were over used to a south, large and area very of low AODs China. ( The AODs observed at the sites in thein southern reaches northeastern of China. the Yangtze River Inof and the at northeast the desert clean China, regions sites the of Alpha northwest values China were and significantly industrial lower region ( dustrial and other anthropogenicof emissions 0.20–0.40 led were observed to inbackground high areas semi-arid aerosol in and north loadings. arid and AOD regions northeast as levels China. well as at some regional in remote regions,Large including AODs the ( Tibetan Plateau and parts of northwestern China. and this was due tonorthwest large and dust north particles China. Alpha transported from semi-arid and arid regions in from summer to winterparticles and were in the main south components China of all the year aerosol populations round,while in suggesting those the that areas. Angstrom fine-mode exponentsof at 0.97 those sites0.61 varied (average from 0.34 0.59–1.29 withPlateau were an 0.37 average to 0.46were and 0.42 0.79 to 0.89, respectively and the corresponding means showed the much higher AODs compared with the rural sites close to deserts or located 5 5 25 20 15 10 15 10 20 25 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | orts would im- ff 12744 12743 This research was funded by the National Key Project of Basic Research orts. First, CARSNET should continue collaborating with other interna- ff Although this work is based on the longest and most extensive set of ground-based enet, G., Lasserre, F., Cachier, H.,aerosols and measured Zhang, in X. spring Y.: Chemical 2002 and atRes., optical the 108, characterization ACE-Asia 8641, of supersite, doi:10.1029/2002JD003214, Zhenbeitai, 2003. China, J. Geophys. properties and chemical composition of theAtmos. atmospheric Environ., aerosol 42, in 6335–6350, urban Guangzhou, 2008. China, characterization of the aerosol opticalJ. properties Quant. over Spectrosc. Loess Ra., Plateau 112, of 346–360, northwestern 2011. China, sky solar irradiance in Badain122, Jaran 194–207, Desert 2013. of northwestern China J. Quant. Spectrosc. Ra., McArthur, L. J. B.: Characterizationbased of sunphotometer atmospheric network: aerosols Aerocan, Atmos. across Ocean., Canada 39, from 429–456, a 2001. ground- Climate forcing by anthropogenic aerosols, Science, 255, 423–430, 1992. Analysis of 40 years of solarL06803, radiation, doi:10.1029/2004GL022322 data 2005. from China, 1961–2000, Geophys. Res. Lett., 32, 2005, Geophys. Res. Lett., 34, L24706, doi:10.1029/2007GL031450, 2007. ison between aerosol optical properties byter a PREDE over skyradiometer Beijing, and CIMEL China, sunphotome- 2008. Atmos. Chem. Phys., 8, 3199–3214,, doi:10.5194/acp-8-3199-2008 Zhou, H. G., Dong,depth F., Li, validation D. of P., andD03206, the Zhou,, doi:10.1029/2008JD011030 China T. 2009a. M.: Aerosol Instrument Remote calibration and Sensing aerosol Network, optical J. Geophys. Res., 114, References Alfaro, S. C., Gomes, L., Rajot, J. L., Lafon, S., Gaudichet, A., Chatenet, B., Maille, M.,Andreae, Caut- M. O., Schmid, O., Yang, H., Chand, D.,Bi, Yu, J., J., Zeng, Huang, L., J., and Fu, Zhang, Q., Y.: Wang, Optical X., Shi,Bi, J., J., Huang, Zhang, J., W., Fu, Huang, Q., Ge, Z., J., and Shi, J., Zhang, Zhou, B.: T., and Toward Bokoye, Zhang, W.: A. Field measurement I., of clear- Royer, A., O’Neill,Charlson, N. R. T., J., Cliche, Schwartz, S. P., E., Fedosejevs,Che, Hales, H. J. G., Z., M., Shi, Teillet, G. Cess, Y., Zhang, P. D., X. Coakley, Y., M., Arimoto, J. R., A., Zhao, and J. and Q., Xu, Hansen, L.,Che, J. Wang, H., B., E.: and Zhang, Chen, X., Z. Li, H.: Y., Zhou, Z.,Che, H., and Shi, Qu, G., Uchiyama, J. A., Yamazaki, J.: A., Chen, Horizontal H., visibility Goloub, P.,and trends Zhang, X.: in Intercompar- China 1981– Che, H., Zhang, X. Y., Chen, H. B., Damiri, B., Goloub, P., Li, Z. Q., Zhang, X. C., Wei, Y., observations of aerosol opticaltowards properties understanding made what in controls Chinaneeded to the in date, aerosol future, it populations. ismonitoring and More just e we detailed a have work first step developed is a set of recommendations for continued well as variations inoptical emissions, and properties the needs interpretationaccount. to of long-term take records both of of aerosol these factors – and possibly others – into tional networks, including AERONET, PHOTONS, RIMA,sistency SKYNET, in etc. calibration to protocols ensure as con- ing well procedures. as Second, cloud-screening the and networktime data should retrieval to be process- obtain expanded and more theInstrument detailed studies information and extended on in site the maintenance aerosol should optical properties be over top China. priorities as these e Collaborative Innovation Center for Climatereceived Change. funding The research from leading the to Europeanunder these Union grant results Seventh agreement has Framework no. Programme 262254. (FP7/2007–2013) (2011CB403401), the ProjectScience (41275167 Foundation and of 41130104) China,of supported Strategic Sciences by Priority (XDA05100301), the and Research CAMS National Program Basis of Natural Research the Project Chinese (2014R17) Academy and the Jiangsu prove data quality and minimizeother gaps key in parameters the data. such Third,tical as in properties single addition of scattering to fine AOD albedo,project mode and size Alpha, particles are distributions should potentially and be valuable thesatellites measured. as for op- The well inter-comparisons as results for with of assimilationthe our into measurements results and current made validation are of with aerosol notdata models. used only Furthermore, to relevant prepare for thetables. China figures for but this also paper have for been East madeAcknowledgements. Asia, available as and Appendix therefore, the 5 5 15 20 25 10 30 10 25 15 20 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | ects Study (CAPES), ff 12746 12745 at Nam,doi:10.1016/j.atmosenv.2010.04.013 2009. Co, a remoteproperties site from Sun and sky indoi:10.1029/2000JD900282, radiance 2000a. measurements, J. central Geophys. Res., 105, Tibetan 20673–20696, Plateau,Accuracy assessments of Atmos. aerosol optical(AERONET) Res., properties Sun retrieved from and 92, Aerosol sky9806, Robotic 2000b. Network radiance 42–48, measurements, J. Geophys. Res.-Atmos., 105,and 9791– Kinne, S.: Wavelength dependencedesert of dust the aerosols, optical J. depth Geophys. of Res., biomass 104, burning, 31333–31349, 1999. urban,Gomes, and L., Zhang, X.optical Y., properties Tsay, at S.tropical C., AERONET mid-Pacific, Ji, sites J. Geophys. Q., in Res., Giles, central 110, D., D06202, eastern doi:10.1029/2004JD005274, and Asia 2005. Slutsker,Singh, and I.: R. aerosol Columnar P., Tripathi, transport S. aerosol N.,Wang, to Reid, P., the and J. S., Xia, Giles, X.:aerosol D. mixtures, Climatological M., J. Dubovik, aspects Geophys. O., of Res., O’Neill, 115, the N. D19205, optical T., doi:10.1029/2010JD014002, Smirnov, properties A., 2010. ofacteristics fine/coarse in mode Beijing6003–6010, during 2009. Olympics Game 2008 in Beijing,integrated China, aerosol Atmos. optical Environ.,4, thickness 43, 330–335, in 2006. Beijing from AERONET observations,physical China properties in Part., an urban and32, suburban 477–486, site doi:10.1007/s00376-014-4097-0, on 2015. the North China Plain, Adv. Atmos. Sci., Theor. Appl. Climatol., 104, 313–324, 2011. Sci. Total Environ, 409, 4934–4938, 2011. tropospheric aerosol by combined lidar andAtmos. sunphotometer Environ., measurements 43, at 2700–2708, Taipei, Taiwan, 2009. and Hao, J.: Impact ofa biomass case burning study on haze in4573-2014, pollution 2014. summer in 2011, the Atmos. Yangtze River Chem. delta, Phys., China: 14,2012. 4573–4585, doi:10.5194/acp-14- the aerosoltions optical over properties three,doi:10.1016/j.atmosenv.2008.11.010 regional 2009b. and background stations their in relationship China, Atmos. withproperties Environ., and 43, aerosol its radiative 1093–1099, forcing564–576, chemical over,10.1007/s00376-009-0564-4 doi: Yulin, 2009c. China composi- in 2001 and 2002, Adv. Atmos.Atmos. Sci., Environ., 26, 45, 6004–6009, 2011. properties over the Taklimakan Desert in China, Aerosol Air Qual.Cuevas-Agulló, Res., E., 13, 777–785, Blarel, 2013. L.,Zhang, X., Wang, and H., Shi, Zhao, G.:ing Column H., a aerosol serious Zhang, optical haze-fog X., propertiesphotometer month measurements, and Wang, over Atmos. aerosol Chem. North Y., Phys., radiative Sun, China 14, forcing2014, 2125–2138, Plain J., dur- 2014. doi:10.5194/acp-14-2125- in Tao, 2013 R., based on ground-based sun- on air quality in Beijing,2010. China, Environ. Eng. Sci., 27, 825–834,, 10.1089/ees.2009.0122 doi: mortality in three Chinese cities: the China Air Pollution and Health E Cong, Z. Y., Kang, S.Dubovik, C., O. and Smirnov, King, M. A., D.: A and flexible inversion Holben, algorithm forDubovik, B.: the O., Smirnov, retrieval A., of Aerosol Holben, B. aerosol N., optical optical King, M. D., properties Kaufman, Y. J., Eck, T. F., and Slutsker, I.: Eck, T. F., Holben, B. N., Reid, J. S.,Eck, Dubovik, T. O., F., Smirnov, Holben, A., B. O’Neill, N., N. Dubovik, T., O., Slutsker, Smirnov, I., A., Goloub, P., Chen,Eck, H. T. F., B., Holben, Chatenet, B. N., B., Sinyuk, A., Pinker, R. T., Goloub, P., Chen, H., Chatenet,Fan, B., S., Li, Tian, Z., G., Li, G., Huang, Y., Qin, J., and Cheng,Fan, S.: Road X., fugitive Chen, dust emission H., char- Goloub, P., Xia, X., Zhang,Fan, X. W., H., and Xia, X. Chatenet, A., B.: and Analysis Chen, H. of B.: column- Comparison ofFu, column-integrated G., Yu, aerosol J., optical Zhang, Y., and and Hu, S.: Temporal variation of wind speed in China for 1961–2007, Chen, W., Chen, Y., Chou, C. K., Chang, S., Lin, P.,and Chen, J.: Columnar optical properties of Cheng, Z., Wang, S., Fu, X., Watson, J. G., Jiang, J., Fu, Q., Chen, C., Xu, B., Yu, J., Chow, J. C., Chin, M.: Atmospheric science: dirtier air from a weaker monsoon, Nat. Geosci., 5, 449–450, Che, H., Yang, Z., Zhang, X., Zhu, C.,Che, H. Ma, Z., Zhang, Q., X. Y., Alfraro, Zhou, S., Chatenet, B., H., Gomes, L., and andChe, Zhao, Wang, H., J. Q.: Wang, Y., Aerosol P.: and optical Sun, Study J.: Aerosol on optical propertiesChe, at H., Mt. Wang, Waliguan observatory, Y., China, Sun, J., Zhang,Che, X., H., Zhang, Xia, X., X., Zhu, and J., Guo, Li, J.: Z., Variation of Dubovik, O., aerosol Holben, optical B., Goloub, P., Chen, H., Estelles, V., Chen, D., Cheng, S., Zhou, Y., Guo, X., Fan, S., andChen, Wang, R., Li, H.: Y., Impact Ma, Y., of Pan, G., road Zeng, fugitive G., dust Xu, X., Chen, B., and Kan, H.: Coarse particles and 5 5 25 10 15 20 30 25 30 10 15 20 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | e, D. A., and Lu, N. M.: ff 12748 12747 ects in northern China, J. Geophys. Res., 112, D22S01,, doi:10.1029/2006JD007382 ff versity Press, New York, 2007. to the Fifth Assessmentby: Report Stocker, T. of F., the Qin, D., IntergovernmentalXia, Plattner, Y., Panel Bex, G.-K., on V., Tignor, and Climate M., Midgley, P. Change, M., Allen, edited Cambridge, S. UK K., and Boschung,Theor. New J., Appl. York, 2013. Nauels, Climatol., A., 99, 421–430, 2010. Aerosol optical properties over eastsurements, Asia J. Geophys. determined Res., from 109, ground-based D02209, sky doi:10.1029/2003JD003387, radiation 2004. mea- Asia determined from ground-basedD10S22, solar, doi:10.1029/2004JD004678 radiation 2005. measurements, J. Geophys. Res., 110, optical depth measurements inRes., 115, eastern D00K11, China doi:10.1029/2009JD012812, and 2010. a new calibrationfor method, China, J. 1990–2005, Geophys. 2011. Atmos. Chem. Phys., 11, 931–954, doi:10.5194/acp-11-931-2011, Sichuan Basin derived from MODIS data, J. Appl. Meteorol.,nese 14, J. 1–7, Atmos. 2003 Sci., (in 19, Chinese). 755–763, 1995 (in Chinese). Urumqi, China Environ. Sci., 25, 22–25, 2005 (in Chinese). Zhao, F. S., Dutton, E.tive G., e and Dickerson,2007. R. E.: Aerosol optical properties and their radia- tors over China for 1961–2000, Ann.2005, Geophys., 23, 2005. 2425–2432, doi:10.5194/angeo-23-2425- Chatenet, B.,photometer Morel, network J.,doi:10.1117/12.783171 overview: P., 2007. Cuevas, description, E., activities, and results,Characterization Ramos, P. of SPIE, R.:ing soil 6936, PHOTONS/AERONET 2001 dust 69360V, sun- ACE-Asia:,doi:10.1029/2002JD002633 aerosol 2003. 2. in Model China simulation and anddistribution validation, its in Wuhan, J. transport China, Atmosphere, Geophys. 5, and Res., 81–91,, doi:10.3390/atmos5010081 distribution 108, 2014. 102, dur- 4262, 6831–6864,, doi:10.1029/96JD03436 1997. century: an alternative scenario, P. Natl. Acad. Sci. USA, 97,aerosol 9875– profiling 9880, with EUCAARI 2000. Ramanseasonal lidar variations, at J. Shangdianzi Geophys. GAW Res., station: 117, Beijing plume D13201, and , doi:10.1029/2012JD017577 2012. Schafer, J., Chatenet, B.,Clark, Lavenue, F., D., Kaufman, Frouin, Y., R., Castle,and Halthore, J. Zibordi, R., V., G.: Karnieli, Setzer, An A., A.,AERONET, emerging J. O’Neill, Markham, ground-based Geophys. N., B., aerosol Res., Pietras, 106, climatology: 12067–12097, C., aerosol 2001. Pinker, optical R., depth Voss, from K., Kaufman, Y., Nakajima, T., Lavenu, F.,ated Jankowiak, instrument I., and network Smirnov, and A.:ron., data AERONET 66, archive – 1–16, for a 1998. aerosol feder- characterization, Remote Sens. Envi- optical characteristics in China266, radiometric 2001 calibration (in site, Chinese). J. Appl. Meteorol. Sci., 12,and 257– Nakajima,ships T.: between An Asiandoi:10.1029/2003JD003550, overview aerosols 2003. and of their ACE-Asia: climatic impacts, strategies J. for Geophys. Res., quantifying 108, the 8633, relation- IPCC: Climate Change 2007: The Scientific Basis, Forth AssessmentIPCC: Report, Climate Cambridge Change Uni- 2013: The Physical Science Basis. Contribution of Working GroupJiang, I Y., Luo, Y., Zhao, Z., and Tao, S.: Changes in windKim, speed D. H., over China Sohn, during B. 1956–2004, J., Nakajima, T., Takamura, T., Takemura, T., Choi, B. C., andKim, Yoon, S. D. C.: H., Sohn, B. J., Nakajima, T., and Takamura,Lee, T.: K., Aerosol Li, radiative Z., forcing Cribb, over M. C., east Liu, J., Wang, L., Zheng, Y.,Lei, Xia, Y., Zhang, X., Q., Chen, He, K. H., B., and and Li, Streets, D. B.: G.: Aerosol Primary anthropogenic aerosol emission trends Li, C. C., Mao, J. T., and Lau, K. H.: Characteristics of theLi, aerosol F. optical and depth distributions Lu, over D.: Optical propertiesLi, of X., atmospheric Chen, Y., aerosols Hu, over X., Mount Ren, Y., Qomolongma, andLi, Chi- Wei, Z. W.: Analysis Q., Xia, of X. atmospheric G., aerosol Cribb, properties M., over Mi, W., Holben, B., Wang, P., Chen, H. B., Tsay, S. C., Eck,Liang, T. F. F., and Xia, X. A.: Long-term trends in solar radiation and the associated climatic fac- Goloub, P., Li, Z., Dubovik, O., Blarel, L., Podvin, T., Jankowiak, I.,Gong, Lecoq, S. R., L., Deroo, Zhang, C., X. Y., Zhao, T. L.,Gong, McKendry, W., Zhang, I. S., and G., Ma, Y.: Aerosol Ja opticalHansen, properties J., and Sato, M., determination and of Ruedy, R.: aerosol Radiative size forcing and climateHansen, response, J. J., Geophys. Sato, Res., M., Ruedy, R., Lacis,Hänel, A., A., and Baars, Oinas, H., V.: Global Althausen, warming D., in Ansmann, the A., twenty-first Engelmann, R.,Holben, and B., Sun, J. Tanre, Y.: D., One-year Smirnov, A., Eck, T., Slutsker, I., Abuhassan, N., Newcomb, W. W., Holben, B. N., Eck, T. F., Slutsker, I., Tanre, D., Buis, J. P.,Setzer, A., Vermote, E., Reagan, J. A., Hu, X., Zhang, Y., Zhang, G., Huang, Y., and Wang, Y.: MeasurementsHuebert, and B. study J., of Bates, aerosol T., Russell, P. B., Shi, G., Kim, Y. J., Kawamura, K., Carmichael, G., 5 5 15 25 10 20 30 15 30 10 20 25 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | ect determined from sky- ff 12750 12749 optical properties based onAtmos. ground Environ., measurements 44, 2587–2596, over 2010. the Chinese Yangtze Delta region, aerosol microphysical properties from AERONETAtmos. Sun Chem. photometer Phys., over 11, southwestern 12535–12547, Spain, , doi:10.5194/acp-11-12535-2011 2011. Environ. Sci., 34, 588–595, 2014 (in Chinese). aerosol optical depthChinese in J. China Atmos. basedChinese). Sci., on 34, meteorological 449–456, horizontal visibility doi:10.3878/j.issn.1006-9895.2010.02.18, observations, 2010tion, (in J. Atmos. Sci., 55, 744–757, 1998. in North China during 1980–1994, Atmos. Environ., 34, 603–609,index 2000. and surface1986. albedo from radiance – part I:aerosol Theory, size distribution Adv. by Atmos.Meteorol. combined Sin., Sci., solar 7, 3, 33–41, extinction 1983. 162–171, and forward scattering method,of Acta the background aerosolinfluences at of regional two transport, sites Tellus B, in 60, southwestern 657–673, and 2008. City northwestern in China: the winter potential of 2007, J. Lanzhou Univ. Nat.dreae, Sci., M. 45, 39–44, O., 2009Collins, (in Cantrell, W. Chinese). D., W., Conant,Howell, Cass, W. S., C., G. Hudson, Dulac, J.,quhar, R., G., Jayaraman, F., Novakov, T., Ogren, Heintzenberg, Chung, A., J. A., Kiehl, J., C.Quinn, Podgorny, I. J. Heymsfield, P. A., K., E., T., Prather, A. Rajeev, K., Krishnamurti, K., Priestley, Clarke, J., K., Rasch, T. Prospero, Holben, J. A. P., N., Rupert, M., B., Lubin, S., D., Sadourny, D., R., Coakley, McFar- Satheesh, J. S. K., A., Shaw, G. E., radiometer over Loess Plateau of,doi:10.5194/acp-11-11455-2011 Northwest 2011. China, Atmos. Chem. Phys., 11, 11455–11463, absorptive properties, Atmos. Chem. Phys., 13,2013. 2253–2265,10.5194/acp-13-2253-2013 , doi: variation of aerosol optical depth14513, over 2001. China in last 30 years, J. Geophys. Res., 106,and 14501– the turbidity, Acta Meteorol. Sin., 41, 322–331, 1983in (in north Chinese). China and its2004. influence on estimating dust emission, Chin. Sci. Bull., 49, 2169–2176, Evaluation ofat the two Moderatedoi:10.1029/2007JD008474, Aerosol 2007. Resolution Robotic Imaging Network stations Spectroradiometer in aerosol China, products J. Geophys. Res., 112, D22S08, east China estimated from visibilityEnviron., measurements 258–267, and,10.1016/j.atmosenv.2014.06.044 doi: chemical 2014. transport modeling, Atmos. characteristic analysis of aerosol opticalScientiae depth Circumstantiae, in 34, the 819–825, atmosphere 2014 of (in Urban Chinese). Chongqing, Acta monsoon on,doi:10.1175/2010JAMC2414.1 aerosol 2011. loading in Eastbased on Asia, the615–632, CE-318 J. 2004 sun (in Appl. Chinese). tracking spectrophotometer Meteorol. data, Clim., J.and Nanjing 50, Inst. Zhang, Meteor., 523–533, B.: 27, Aerosol optical properties and radiative e Pan, L., Che, H., Geng, F., Xia, X., Wang, Y., Zhu, C., Chen, M., Gao,Prats, W., N., and Guo, Cachorro, J.: V. Aerosol E., Berjón, A., Toledano, C., and De Frutos,Qi, A. B., M.: Du, Column-integrated R., Yu, Z., andQin, Zhou, S., B.: Aerosol Shi, optical G., depth Chen, in L., urban Wang, site B., of Zhao, Hangzhou, J., China Yu, C., andQiu, Yang, J.: S.: A method Long-term to variation determine atmospheric of aerosol opticalQiu, depth J. using and total Yang, L.: direct Variation characteristics solar of radia- atmospheric aerosol optical depthsQiu, and visibility J. and Zhou, X.: Simultaneous determination of aerosolQiu, size J., distribution Wang, H., and Zhou, refractive X., and Lu, D.: Experimental study of remoteQu, sensing W., Zhang, of atmospheric Y., Arimoto, R., Wang, D., Wang, Y., Yan, Y., and Li, Y.:Quan, Chemical X., composition Zhang, L., Cao, X., and Wang,Ramanathan, H.: V., Property Crutzen, of P. aerosol J., optical Lelieveld, depth J., over Mitra, Lanzhou A. P., Althausen, D., Anderson, J., An- Logan, T., Xi, B., Dong, X., Li, Z., and Cribb, M.: Classification and investigation of Asian aerosol Luo, Y., Lu, D., Zhou, X., Li, W., and He, Q.: Characteristics of the spatial distributionMao, and J., yearly Wang, Q., and Zhao, B.: TheMei, observation F., of Zhang, X., the Lu, atmospheric H., transparency Shen, spectrum Z., and Wang, Y.: Characterization of MASDsMi, of surface W., soils Li, Z., and Xia, X., Holben, B., Levy, R., Zhao, F., Chen, H., and Cribb, M.: Lin, J., van Donkelaarb, A., Xin, J., Che, H., and Wang, Y.: Clear-sky aerosol opticalLiu, depth over R., Li, L., Yu, J., Huang, W., Xu, L.,Liu, Liu, M., X., and Yan, Tang, X.: L., On-line measurements Yang, and P.,Liu, Y., Yin, Niu, S., and Z., Zheng, Y.: Optical and depth characteristics North, of Yinchuan atmospheric G., aerosols Liu, R.: Y., Huang, Influence J., Shi, of G., indian Takamura, T., summer Khatri, P., Bi, J., Shi, J., Wang, T., Wang, X., 5 5 15 20 10 25 30 20 25 15 30 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | E) ◦ N, 117.17 ◦ ects of Asian dust and pollution, B. Am. ff 12751 12752 , S. T., Wang, M. Q., Bond, T. C., and Bo, Y.: Black carbon ff ects of the great Indo–Asian haze, J. Geophys. Res., 106, 28371–28398, ff emissions in China, Atmos. Environ., 35, 4281–4296, 2001. during summer and autumn2014. of 2012 in Xi’an, China, Aerosol Airthe Pearl Qual. River Res., Delta, 14, Acta Scientiae 850–861, Circumstantiae, 29, 1146–1155,Wang, 2009 (in H., Chinese). and Zhang,Cimel X. sunphotometers Y.: in Development Chinadoi:10.1016/j.partic.2013.04.009, of aerosol 2014. an remote integrating sensing sphere network, calibration Particuology, 13, method 88–99, for served by sky-radiometer inJpn., 83A, the 291–305, Intensive 2005. Observation Period 1 (IOP1),desert J. in spring, Meteorol. Chinese Soc. J. Atmos. Sci., 12, 75–81,polarization 1988 measurements (in of Chinese). a sun photometer, Int. J. Remote Sens., 33, 69–80, 2012. optical properties of regional44, background 4404–4412,, atmosphere doi:10.1016/j.atmosenv.2010.07.043 2010. in northeast China, Atmos. Environ., erties over northwest ChinaD00K27, doi:10.1029/2009JD013467, during 2010. ARM China 2008 deployment, J.characteristics Geophys. of Res., aerosol 115, optical properties at the SKYNET Hefei site (31.90 from 2007 to 2013, J.2014. Geophys. Res.-Atmos., 119, 6128–6139, doi:10.1002/2014JD021500, Jungfraujoch and Mauna Loa,Switzerland, in: 70–71, Proceedings 2002. of ARJ Workshop, SANW Congress, Davos, phys., 28, 1121–1132, doi:10.5194/angeo-28-1121-2010, 2010. spatial and temporal variations over north China in springsolar 2001, irradiance Tellus induced B, by 57, aerosols 28–39, inRes., 2005. a 112, suburban 1–9, region 2007. in northeastern China, J. Geophys. over Hangzhou using remote2011 sensing (in data, Chinese). Acta Scientiae Circumstantiae, 31, 1758–1767, product over China using CARSNET measurements, Atmos. Environ., 45, 5970–5978, 2011. Sun, Y., and Hu,served B.: by Aerosol optical theJ. depth Chinese Geophys. (AOD) Res., Sun 112, and D05203, Hazemeter Angstrom doi:10.1029/2006JD007075, exponent Network 2007. of from aerosolssummer August ob- monsoon 2004 circulation, toSci., and September 46, precipitation 279–286, 2005, 2010. over northeast Asia, Asia Pac. J. Atmos. Meteorol. Soc., 85, 367–380, 2004. pounds measured inJ. Geophys. summer Res., 114, in D00G06, Beijing, doi:10.1029/2008JD010863 2009. and theircontrol algorithms role for the in AERONET database, ground-level Remote Sens. ozone Environ., 73, formation, 337–349, 2000. 2001. Cahill, T. A., Clarke,icz, K. A. M., Quinn, D., P. K., Doherty,Tang, Russell, Y. S. L. H., M., J., Russell, Uno, P. Flatau, B.,ASIA: I., Shimizu, regional P. Vogelmann, A., climatic J., Shinozuka, A. and Y., Huebert, Song, atmospheric M., C. chemical B. Weber, H., e R. J., J., Kim, Woo, J., J. Markow- H., and Zhang, X. Y.: ACE- Sheridan, P., and Valero, F. P. J.:mate Indian forcing Ocean and Experiment: e an integrated analysis of the cli- Xia, X.: A closer looking at dimming and brightening in China during 1961–2005, Ann.Xia, X. Geo- A., Chen, H. B., Li, Z. Q., Wang, P. C., and Wang, J. K.: Significant reduction of surface Xie, Y., Zhang, Y., Xiong, X., Qu, J. J., and Che, H.: Validation of MODIS aerosol optical depth Yoon, S., Kim, S., Choi, S., and Choi, I.: Regional-scale relationships between aerosol and Wehrli, C.: Calibration of filter radiometers for the GAW Aerosol Optical Depth Network at Xia, X. A., Chen, H. B., Wang, P. C., Zong, X. M., and Gouloub, P.: Aerosol properties and their Xiao, Z., Jiang, H., Chen, J., Wang, B., and Jiang, Z.: Monitoring the aerosol optical properties Xin, J., Wang, Y., Li, Z., Wang, P., Hao, W., Nordgren, B., Wang, S., Liu, G., Wang, L., Wen, T., Su, X., Cao, J., Li, Z., Lin, M., andTan, Wang, H., G.: Wu, D., Column-integrated Deng, X., aerosol Bi, optical X., Li, properties F., andTao, Deng, R., T.: Observation Che, of H. aerosol optical Z., depth Chen, over Q. L., Wang, Y. Q., Sun, J.Uchiyama, Y., A., Zhang, Yamazaki, X. A., C., Togawa, Lu, H., S., and Guo, Asano, J. J.: Characteristics P., ofWang, aeolian D. dust and ob- Qiu, J.: TheWang, study J., of Yang, S., atmospheric Zhao, aerosol Q., optical and Cui, properties S.: in Analyses Takla-Makan of aerosol properties in Hefei based on Wang, P., Che, H., Zhang, X., Song, Q., Wang, Y.,Wang, Zhang, X., Huang, Z., J., Dai, Zhang, X., R., Chen, and B., Yu, and D.: Bi, Aerosol J.: Surface measurementsWang, Z., of Liu, aerosol D., prop- Wang, Z., Wang, Y., Khatri, P., Zhou, J., Takamura, T., and Shi, G.: Seasonal Shao, M., Lu, S., Liu, Y., Xie, X., Chang, C., Huang,Smirnov, A., S., Holben, and B. Chen, N., Eck, Z.: T. F., Volatile Dubovik, O., organic and com- Slutsker,Streets, I.: D. Cloud G., screening Gupta, and quality S., Waldho Seinfeld, J. H., Carmichael, G. R., Arimoto, R., Conant, W. C., Brechtel, F. J., Bates, T. S., 5 5 20 15 25 30 30 10 15 20 25 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | erent ff Obs. days 12754 12753 Urban sites (21 sites) Remote sites (4 sites) Rural sites in eastern China (10 sites) Rural sites on or near the Chinese Loess Plateau (4 sites) Rural sites near the northern and northwestern deserts of China (11 sites) Site information for the 50 CARSNET sites used in this study. No. Site Name1 Long.2 Akedala3 Lat. Lhasa4 Mt. Waliguan 47.12 Shangri-La 36.28 Alt.5 100.92 87.97 Site 29.67 information 6 28.02 3810.0 Dunhuang7 562.0 91.13 In 99.73 the Ejina east8 55 km edge 3663.0 west of 3583.0 of Qinghai-Xizang 40.15 Hami Fuhai Plateau,9 county, Qinghai Xinjiang In Province, province, 12 the Global km and center Hotan GAW northeast 250–300 station10 of km of 94.68 Lhasa southeast Shangri-La city, of county Qinghai-Xizang Kazakestan. Jiuquan (Diqing Plateau.11 area, 1139.0 Yunnan Minqin province, China) 41.9512 1.5 Tazhong km northeast 42.82 101.07 of13 Dunhuang Ulate city, 37.13 Gansu 39.77 province; near14 93.52 Kumutage 940.5 Xilinhot Desert 464 of 38.63 79.93 China 39.0015 98.48 West Zhangbei ofIner-Mongolia 737.0 Province, 103.08 1374.7 near Mongolia 470 1477.3 Zhurihe and 83.67 Badanjilin 500 1367.0 km desert Sourth east edge 5 from 41.57 km of 1099.4 43.95 Urumuqi,In16 north Takilamakan Hami 41.15 In Desert, of county, Minqin 1000 Jiuquan nearby km county, 108.52 City, the east south In Gansu 116.1217 Gobi to from the Province, 114.70 desert, Tenggeli Dongsheng Urumuqi, middle nearby desert Xinjiang Xinjiang the of and 1288.0 Province Province Badanjilin Takilamakan 42.40 north 1003.0 Desert,18 Desert to 1093.4 Xinjiang Mt. Badanjilin Province 2370 Gaolan 701 Desert, Northwest 112.90 39.83 Gansu 5 ofInner-Mongolia,19 km Province 40 butIn southeast Yanan km grass of north desertification Xilinhot of 1152.0 109.98 region City,Inner-Mongolia Zhangjiakou Province, City 36.00 Yulin and Hebei near Province, Hunshandake In 1460.5 and sand-land the near middle 103.85 Hunshandake20 ofInner sand-land mongolia In Province, the and 2161.6 center nearby21 of Hunshandake 1435 36.60 Changde Erdos sand-land 685 city,Innermogolia province. 612 5 km22 north 109.50 Dongtan 2228 from Lanzhou 38.43 city,Gansu23 province. Gucheng 958.5 29.17 109.2024 Huimin 2 111.70 1135.0 2250 km25 31.52 northeast Lin’an of 830 Yan’an city, 39.13 10 Shaanxi km26 121.96 Provice 219 north 565.0 412 Mt. of Longfeng Yulin 115.80 city, Shaanxi27 province 18 Mt. km 44.73 Tai 37.48 northwest from 10.028 Changde Shangdianzi city, Hunan 127.60 117.53 45.2 province. 30.30 In29 the Tongyu Chongmin 365 40.65 Island, Within 30 119.73 area 330.5 km of east Yushe rapid of 11.7 117.12 urbanization,38 Shanghai km 36.25 city In southwest of Wuchang 138.6 county, Baoding30 100 175 km city, km Hebei 117.10 Northeast northeast 293.0 province. of of 712 Jinan 44.42 150 Harbin31 km City, city, Shandong northeast Anshan Heilongjiang 1591.0 1984 Province of In Province Shanghai, Miyun 122.8732 and county, 150 50 km 37.07 Beijing At km northeast summit west to of of33 Beijing Mt. Hangzhou city. Tai, city, 112.98 Benxi 151.0 middle Zhejiang of province northern34 China 1041.5 Chengdu 41.08 In Plain,Shandong Tonyu Province county, west35 of 1.5 Jilin Dalian 123.00 km Province 39.80 east of36 Yushe county, Datong Shanxi Province 116.47 30.65 750 37 41.32 23.0 Fushu 104.0338 123.78 In Hangzhou the 31.3 center 234 38.90 of39 1029 Anshan 496.0 Hefei city, 40.10 183.0 Liaoning In 121.63 province. the40 southeast In of 1357 Kunming 30.23 113.33 the Beijing In center center the 41.88 of at41 center Chengdu city of 766 Lanzhou 120.17 city, margin Benxi 1067.3 Sichuan city, 91.5 province. 123.95 Liaoning42 province. Nanjing 9 km Southeast of 25.01 of43 Datong Dalian 31.98 42.0 Cinty, Nanning center but at within 80.0 102.65 city area 36.0544 margin, of 218 116.38 In 210 Panyu Liaoning rapid the Province urbanization, 173 center In Shanxi 1889.0 103.88 of45 the Province Hangzhou center Pudong 32.05 city, of Zhengjiang Fushun province. In city, 1517.346 22.82 Liaoning the 92.0 province. Shenyang 118.77 west region 451 of 374 In47 Kunming 108.35 In the city, Tianjin the Yunnan center province center of of Lanzhou48 Hefei city, 99.3 Gansu city, 31.22 Urumqi 41.77 Anhui province. 172.0 province. 2349 851 In 121.55 Xi’an 123.50 the In center Nanning 113.35 of city,50 Guangxi Nanjing Yinchuan province city, Jiangsu 39.10 province 14.0 Zhengzhou 60.0 2042 145.0 43.78 117.17 In In In Pudong the Panyu district 38.48 center district of 87.62 34.78 of of Shanghai Shenyang 34.43 Guangzhou city 2269 city, city, Liaoning 106.22 Guangdong province. Province 113.68 3.3 108.97 935.0 1111.5 In the In center the In 363.0 of center 99.0 the Tianjin 1045 of center City. Urumuqi of city, Yinchuan Xijiang 20 city, km In province Ningxia north the province. center of of center Zhengzhou of city, Xian 738 Henan city, province. but within Jing 763 230 RiverIndustrial District, Shaa areas of China, Adv. Atmos. Sci., 19, 136–152, 2002. loading over theEnviron., Bohai, doi:10.1016/j.atmosenv.2015.03.048 in Bay press, as 2015. revealed by groundAtmospheric and aerosol compositions satellite in remoteregional China: spatial/temporal sensing, haze variability, distribution Atmos. chemical and signature, 779–799, comparisons doi:10.5194/acp-12-779-2012 , 2012. with global aerosols, Atmos. Chem. Phys.,vapor, Sci. 12, China Ser. B, 10, 951–962, 1983 (in Chinese). visibility and particulate matter (PM)4, in 427–434, an, doi:10.5094/APR.2013.049 urban 2013a. area of Northeast China, Atmos.optical Poll. properties Res., over urban andsun-photometer industrial region measurement, of Atmos. northeast Environ., China 75, by 270–278, using 2013b. ground-based the decadal-scale weakening of theL09809, East doi:10.1029/2012GL051428 , Asian 2012. summer monsoon, Geophys. Res. Lett., 39, optical and physical propertiesAtmos. at Environ., a 84, 54–64, regional, doi:10.1016/j.atmosenv.2013.11.019 background 2014. atmosphere in North China Plain, Zhang, X. Y., Wang, Y. Q., Niu, T., Zhang, X. C., Gong, S. L.,Zhao, Zhang, B., Y. Wang, Q., M., Mao, and J., and Sun, Qin, J. Y.: Study Y.: onZhao, remote H., sensing of Che, aerosol H., optical depth Zhang, and X., Ma, Y., Wang, Y., Wang,Zhao, H., H., Che, and H., Zhang, Wang, X., Y.: Ma, Characteristics Y., Wang, Y., of Wang, X., Liu, C., Hou, B., andZhu, Che, H.: J., Aerosol Liao, H., and Li, J.: Increases in aerosol concentrations over eastern China due to Zhu, J., Che, H., Xia, X., Chen, H., Goloub, P., and Zhang, W.: Column-integrated aerosol Table A1. Zhang, J., Chen, J., Xia, X., Che, H., Fan, X., Xie, Y., Chen, H., and Lu, D.: Heavy aerosol Zhang, J., Mao, J., and Wang, M.: Analysis of aerosol extinction characteristics in di 5 10 15 20 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 12756 12755 Annual Spring Summer Fall Winter Annual Spring Summer Fall Winter SD 0.15SD 0.19 0.02 0.15SD 0.09 0.09 0.05 0.05 0.07SD 0.08 0.12 0.08 0.06 0.29 0.03 0.19SD 0.05 0.07 0.03 0.16 0.06 0.14 0.10 0.09 0.10SD 0.03 0.06 0.15 0.08 0.09 0.03 0.16 0.26 0.07 0.06 0.05SD 0.03 0.09 0.30 0.03 0.06 0.14 0.02 0.31 0.11 0.06 0.17 0.06SD 0.02 0.29 0.02 0.04 0.14 0.15 0.19 0.05 0.17 0.03 0.20 0.27SD 0.24 0.04 0.08 0.04 0.21 0.43 0.22 0.03 0.18 0.15 0.18 0.14SD 0.16 0.02 0.22 0.30 0.18 0.12 0.08 0.26 0.11 0.20 0.12 0.18SD 0.10 0.30 0.09 0.14 0.14 0.18 0.23 0.09 0.12 0.13 0.26 0.11SD 0.20 0.12 0.10 0.12 0.39 0.26 0.19 0.09 0.21 0.24 0.17 0.22SD 0.12 0.11 0.26 0.20 0.20 0.40 0.09 0.13 0.15 0.18 0.33 0.23SD 0.14 0.29 0.13 0.23 0.41 0.19 0.21 0.09 0.31 0.24 0.09 0.23SD 0.15 0.14 0.27 0.22 0.15 0.24 0.22 0.23 0.10 0.27 0.40SD 0.25 0.19 0.11 0.42 0.46 0.26 0.12 0.15 0.04 0.43 0.37SD 0.41 0.23 0.11 0.22 0.13 0.45 0.33 0.18 0.09 0.35 0.48 0.32 0.27SD 0.14 0.14 0.24 0.43 0.29 0.26 0.13 0.22 0.48 0.26 0.24 0.28SD 0.14 0.44 0.39 0.16 0.24 0.26 0.28 0.36 0.21 0.16 0.16 0.15SD 0.29 0.28 0.24 0.17 0.24 0.29 0.32 0.12 0.28 0.17 0.28 0.39SD 0.19 0.10 0.26 0.27 0.29 0.34 0.08 0.22 0.18 0.27 0.35 0.32SD 0.15 0.17 0.20 0.14 0.26 0.34 0.19 0.35 0.22 0.20 0.47 0.32SD 0.18 0.26 0.22 0.18 0.23 0.42 0.20 0.11 0.24 0.24 0.37 0.14SD 0.14 0.12 0.29 0.24 0.42 0.20 0.12 0.21 0.21 0.46 0.37 0.24SD 0.21 0.29 0.22 0.26 0.43 0.23 0.23 0.37 0.35 0.30 0.32 0.19 0.23 0.44 0.39 0.33 0.22 0.34 0.25 0.24 0.45 0.19 0.31 0.26 0.30 0.43 0.50 0.22 0.20 0.39 0.45 0.21 0.59 0.39 – 0.51 0.21 0.08 0.45 0.23 0.19 0.45 0.30 0.05 0.41 0.27 0.35 0.30 Site AOD Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec No. Name12 Akedala3 Anshan4 Beijing5 Benxi6 0.20 Changde7 0.70 Chengdu8 0.21 Dalian9 0.76 0.77 Datong AOD10 0.59 0.85 Dongsheng 0.83 0.2311 0.98 Dongtan 0.1512 0.63 0.82 0.82 Dunhuang13 1.08 0.62 0.54 Ejina 0.46 0.92 0.22 0.5114 Fushu 0.63 0.44 1.03 0.58 0.6215 0.64 0.50 0.32 Gucheng 0.99 0.61 0.49 0.6516 0.65 Hami 0.68 1.13 0.6217 0.48 0.69 Hangzhou 0.68 1.03 0.61 0.7918 0.57 0.25 1.16 Hefei 0.92 0.50 0.38 0.70 0.4919 1.01 0.44 0.67 Hotan 0.32 0.8320 0.36 1.18 0.49 Huimin 1.01 0.40 0.34 0.73 0.52 0.21 0.49 0.85 1.1221 0.52 0.25 1.09 Jiuquan 1.1322 0.89 0.69 1.07 0.85 Jurih 0.62 0.28 0.27 0.3123 0.72 0.96 0.55 0.96 0.83 1.13 Kunming 0.79 1.15 0.18 1.33 0.61 0.8424 0.69 0.47 Lanzhou 1.08 0.71 1.31 0.88 0.61 0.96 0.8925 1.13 1.12 0.56 0.31 Lhasa 0.46 0.18 0.24 1.17 1.35 1.02 0.75 0.68 0.68 0.76 0.4426 Alpha 0.97 Lin’an 0.74 0.20 1.14 0.41 1.0827 0.43 0.29 0.24 Minqin 1.18 1.07 0.82 1.24 0.59 1.03 0.8028 0.75 0.26 0.93 Mt. 0.57 1.09 0.77 Gaolan 1.27 0.53 0.78 1.24 0.79 0.8429 0.29 0.37 0.89 Mt. 1.24 0.29 Longfeng 0.40 0.79 0.11 0.6630 0.37 0.85 Mt. 1.11 1.24 0.98 0.79 0.21 Tai 1.11 0.55 0.85 0.7831 0.51 0.87 0.57 0.62 0.46 Mt. 0.34 Waliguan 0.65 0.36 0.16 0.3932 1.11 0.35 1.17 0.59 0.30 Nanjing 0.59 0.18 0.56 0.8033 0.54 0.55 1.28 0.93 0.80 1.19 0.40 Nanning 0.46 0.14 0.68 0.18 0.2234 1.31 0.12 0.94 Panyu 0.14 1.14 1.24 0.3335 1.01 0.99 0.09 0.75 0.50 0.21 Pudong 0.67 0.71 0.41 1.31 0.09 0.34 1.27 36 0.94 0.44 0.79 0.89 Shangdianzi 0.96 0.57 0.43 0.36 0.29 1.24 0.0937 0.35 0.82 0.39 Shangri-La 0.80 1.24 1.23 0.1738 0.92 0.77 0.90 0.10 Shenyang 0.66 0.46 0.48 1.29 0.31 1.33 0.78 0.29 0.09 0.99 1.2539 0.51 0.57 0.80 0.30 Tazhong 0.48 0.64 0.89 1.2740 0.11 0.29 Tianjin 0.55 1.26 0.96 0.09 0.49 1.24 1.2741 0.89 0.48 0.98 Tongyu 0.73 0.78 0.76 1.38 0.69 1.09 0.83 0.67 0.54 0.13 0.1742 1.19 Ulate 0.98 0.82 0.65 0.80 1.10 0.63 0.5443 0.53 0.59 0.80 Urumqi 1.06 1.32 0.73 0.37 0.59 0.99 0.4244 1.48 0.81 0.74 1.01 Xi’an 0.15 1.01 0.64 0.74 0.81 1.0545 0.98 1.10 1.32 Xilinhot 0.26 0.34 0.09 0.33 0.86 0.86 0.81 1.4446 0.51 1.39 Yanan 0.68 1.24 0.78 0.85 0.74 0.59 1.4247 0.78 0.58 1.50 0.33 0.06 0.28 0.66 Yinchuan 0.47 0.7548 1.29 1.03 0.34 Yulin 0.83 0.79 1.11 1.35 1.36 0.68 0.72 1.45 0.3449 0.89 1.16 0.48 0.90 Yushe 1.26 0.26 0.3250 0.33 0.67 1.26 1.14 Zhangbei 0.96 1.37 0.52 0.23 0.54 1.32 0.37 0.89 1.12 0.32 Zhengzhou 1.41 0.88 0.36 1.35 0.27 0.64 1.16 1.18 1.58 0.56 0.16 0.21 0.38 0.39 1.20 0.29 1.30 0.90 0.38 1.28 0.98 0.30 1.27 0.33 0.58 1.17 0.94 1.42 1.57 0.23 1.28 0.73 0.83 1.34 0.19 1.08 0.10 0.53 0.41 0.41 1.35 0.33 1.39 0.57 1.10 0.94 0.98 1.35 0.49 0.37 0.90 1.30 0.19 0.92 1.05 1.14 1.19 0.75 0.15 0.96 0.50 0.50 0.34 0.36 0.77 1.08 0.38 0.84 0.27 0.30 0.64 1.17 0.49 0.87 0.81 0.89 0.79 1.20 0.51 1.16 0.34 0.87 1.26 0.24 0.89 0.48 0.87 0.70 0.75 0.86 0.94 1.07 0.66 1.79 0.73 0.63 1.01 0.82 1.02 0.56 0.88 1.02 1.10 0.77 1.08 0.94 0.79 0.98 1.01 0.60 0.50 0.79 0.85 0.90 1.04 0.92 0.75 0.93 0.93 0.87 0.64 1.19 1.23 0.96 0.58 1.09 1.20 0.79 0.52 1.04 1.10 1 Akedala2 Lhasa3 Mean 0.16 Mt. Waliguan4 0.28 Mean Mean 0.24 Shangri-La 0.095 0.08 0.21 0.13 0.12 Mean 0.17 Ejina 0.246 0.15 0.06 0.20 0.23 0.18 0.07 0.33 Zhurihe 0.187 0.14 0.17 0.15 0.18 0.13 0.13 0.16 Mean Hami 0.198 0.12 0.10 0.12 0.18 Mean 0.16 0.11 0.08 0.16 0.21 Xilinhot 0.11 0.129 0.10 0.17 0.20 0.34 0.17 0.10 0.08 0.19 Mean 0.39 Wulate 0.17 0.0610 0.08 0.14 0.27 0.35 0.27 Mean 0.05 Zhangbei 0.08 0.08 0.29 0.29 0.42 0.2211 0.07 0.35 0.26 0.49 0.18 Mean Jiuquan 0.05 0.30 Mean 0.27 0.34 0.26 0.2312 0.28 0.18 0.23 0.27 0.33 0.24 Dunhuang 0.34 0.20 0.16 0.22 0.39 0.30 Mean13 0.19 0.25 0.14 0.18 0.39 0.33 0.28 Mean Minqin 0.18 0.32 0.16 0.13 0.32 0.39 0.39 0.2614 0.18 0.41 0.13 0.28 0.44 0.36 0.33 Tazhong 0.21 0.45 0.23 0.35 0.55 0.4815 0.22 0.27 Mean 0.18 0.28 0.36 0.55 Hotan 0.23 0.35 0.26 0.16 Mean 0.24 0.33 0.4116 0.32 0.35 0.18 0.30 0.21 0.27 0.35 Dongsheng 0.27 0.48 0.44 0.19 0.28 0.3417 0.48 Mean 0.75 Mean 0.21 0.24 0.25 Yulin 0.43 0.29 0.91 0.45 0.23 0.2318 0.43 0.41 0.77 0.71 0.17 0.33 0.21 Yan’an 0.45 0.47 0.73 0.71 0.24 0.2019 0.44 0.55 0.64 0.74 Mean 0.25 Mt. Gaolan 0.39 0.47 0.61 0.81 0.3320 Mean 0.36 0.72 0.51 0.72 0.42 Mean Yushe 0.38 0.29 0.55 0.30 0.72 0.39 0.4521 0.38 0.27 0.56 0.22 0.81 0.45 0.55 Changde 0.35 0.52 0.26 0.60 0.39 0.5822 0.43 Mean 0.36 0.43 0.49 0.59 Mt. Longfeng 0.38 Mean 0.53 0.26 0.31 0.49 0.4923 Mean 0.44 0.82 0.52 0.31 0.37 0.54 0.42 Mt. 0.32 Tai 0.39 0.73 0.52 0.37 0.4024 0.31 0.39 0.82 0.62 0.21 0.41 Dongtan 0.32 0.46 0.58 0.55 0.23 0.4625 0.46 0.39 0.49 0.69 Mean 0.26 0.45 Shangdianzi 0.41 0.25 0.45 0.75 0.15 Mean 0.38 0.42 0.26 Mean 0.40 0.86 0.28 0.64 0.38 0.30 0.32 0.47 0.71 0.28 0.83 0.30 0.37 0.70 0.39 0.37 0.70 0.27 0.49 0.56 0.37 0.42 0.64 0.32 0.57 0.57 0.40 0.58 0.51 0.29 0.58 0.51 0.51 0.67 0.30 0.72 0.43 0.58 0.56 0.78 0.60 – 0.40 0.51 0.15 0.44 0.43 0.16 0.62 0.34 0.09 0.59 0.31 Data of Figs. 5–15: AOD. Data for Figs. 2 and 3. Table A3. Table A2. Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 12758 12757 SD 0.39SD 0.37 0.32 0.67SD 0.25 0.31 0.20 0.26 0.33SD 0.24 0.28 0.23 0.23 0.24 0.36 0.14SD 0.27 0.22 0.33 0.22 0.32 0.35 0.37 0.37 0.33SD 0.35 0.44 0.34 0.33 0.26 0.25 0.46 0.27 0.41 0.38 0.28SD 0.26 0.39 0.25 0.39 0.32 0.40 0.22 0.26 0.27 0.24 0.25 0.19SD 0.27 0.29 0.29 0.27 0.24 0.30 0.32 0.39 0.35 0.28 0.27 0.45SD 0.32 0.44 0.48 0.33 0.37 0.35 0.34 0.41 0.48 0.45 0.35 0.36SD 0.29 0.44 0.44 0.35 0.51 0.27 0.33 0.40 0.30 0.36 0.20 0.28SD 0.37 0.42 0.29 0.38 0.19 0.24 0.39 0.34 0.44 0.17 0.44 0.25SD 0.41 0.28 0.30 0.15 0.45 0.39 0.44 0.28 0.25 0.47 0.27 0.24SD 0.46 0.25 0.19 0.42 0.30 0.29 0.42 0.22 0.42 0.36 0.21 0.30SD 0.35 0.33 0.31 0.31 0.22 0.33 0.31 0.37 0.25 0.23 0.26 0.32SD 0.28 0.36 0.21 0.23 0.25 0.29 0.26 0.30 0.12 0.26 0.08SD 0.23 0.28 0.18 0.13 0.06 0.30 0.29 0.20 0.17 0.14 0.07SD 0.22 0.25 0.24 0.27 0.24 0.07 0.07 0.35 0.28 0.27 0.06 0.09 0.37SD 0.32 0.33 0.33 0.07 0.11 0.22 0.41 0.30 0.13 0.09 0.21 0.31SD 0.40 0.29 0.06 0.19 0.28 0.32 0.28 0.07 0.31 0.27 0.23 0.26SD 0.39 0.10 0.31 0.34 0.28 0.36 0.35 0.16 0.30 0.27 0.35 0.27SD 0.30 0.20 0.28 0.24 0.23 0.27 0.29 0.30 0.35 0.33 0.12 0.31SD 0.25 0.40 0.15 0.29 0.20 0.34 0.38 0.25 0.28 0.27 0.39 0.34SD 0.31 0.25 0.34 0.30 0.25 0.29 0.29 0.23 0.36 0.29 0.23 0.41SD 0.26 0.29 0.36 0.11 0.26 0.35 0.36 0.38 0.27 0.30 0.24 0.34SD 0.32 0.30 0.30 0.26 0.34 0.35 0.29 0.16 0.29 0.26 0.26 0.07 0.26 0.24 0.31 0.34 0.26 0.13 0.33 0.20 0.35 0.24 0.17 0.35 0.23 0.36 0.28 0.12 0.29 0.40 0.41 0.29 0.29 0.23 0.26 0.31 0.22 0.26 0.28 0.23 0.26 0.28 0.37 0.26 0.32 0.31 0.34 SD 0.32SD 0.32 0.36 0.45SD 0.29 0.47 0.29 0.33 0.45SD 0.31 0.30 0.45 0.31 0.16 0.29 0.48SD 0.33 0.06 0.31 0.53 0.37 0.19 0.29 0.46 0.37SD 0.39 0.33 0.32 0.34 0.40 0.32 0.44 0.34 0.46 0.32 0.31SD 0.35 0.42 0.32 0.48 0.31 0.20 0.26 0.34 0.28 0.45 0.25 0.21SD 0.14 0.35 0.24 0.38 0.26 0.13 0.14 0.29 0.30 0.32 0.14 0.25SD 0.34 0.29 0.17 0.37 0.10 0.32 0.13 0.17 0.41 0.13 0.46 0.37SD 0.18 0.22 0.37 0.15 0.49 0.36 0.22 0.33 0.51 0.28 0.49 0.24SD 0.16 0.22 0.47 0.37 0.45 0.34 0.19 0.20 0.58 0.44 0.41 0.24SD 0.14 0.27 0.49 0.57 0.29 0.22 0.27 0.50 0.49 0.42 0.31 0.33SD 0.24 0.48 0.49 0.36 0.30 0.40 0.54 0.44 0.49 0.33 0.37 0.29SD 0.49 0.48 0.42 0.33 0.29 0.30 0.51 0.39 0.32 0.23 0.39 0.52SD 0.53 0.37 0.31 0.16 0.52 0.47 0.46 0.34 0.22 0.34 0.38 0.44SD 0.45 0.34 0.23 0.51 0.49 0.45 0.34 0.22 0.50 0.28 0.40 0.51SD 0.43 0.21 0.39 0.27 0.39 0.49 0.38 0.30 0.47 0.37 0.40 0.27SD 0.41 0.34 0.55 0.30 0.45 0.35 0.39 0.34 0.51 0.50 0.22 0.34SD 0.33 0.68 0.38 0.46 0.26 0.31 0.69 0.33 0.40 0.28 0.59 0.09SD 0.48 0.19 0.42 0.25 0.61 0.09 0.48 0.29 0.21 0.53 0.25 0.28SD 0.55 0.36 0.18 0.55 0.28 0.29 0.44 0.34 0.40 0.26 0.36 0.26SD 0.38 0.24 0.34 0.46 0.32 0.27 0.25 0.30 0.68 0.26 0.27SD 0.18 0.37 0.18 0.18 0.42 0.40 0.42 0.35 0.48 0.28SD 0.40 0.21 0.34 0.17 0.41 0.43 0.48 0.42 0.08 0.17SD 0.34 0.49 0.41 0.15 0.36 0.33 0.17 0.25 0.43 0.42 0.32 0.50 0.31 0.30 0.41 0.13 0.34 0.51 0.24 0.37 0.28 0.43 0.29 0.40 0.41 0.42 0.42 0.42 0.40 0.21 0.31 0.37 0.39 0.31 0.39 0.34 0.32 0.22 0.14 0.50 0.41 0.36 0.44 0.07 0.39 0.18 0.33 0.25 Site AOD Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Site Alpha Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 26 Huimin27 Gucheng Mean28 0.64 Mean Lin’an 0.72 0.6629 0.72 0.77 Tongyu 0.81 0.65 Mean30 0.71 0.77 0.83 Urumqi Mean 0.90 0.76 0.8431 0.18 0.78 0.81 0.81 Datong 0.13 Mean 0.70 0.76 0.8132 0.21 0.71 0.68 0.59 0.78 Yinchuan 0.35 Mean 0.85 0.69 0.79 0.9633 0.44 0.55 0.63 0.62 Mean 0.64 0.58 Dalian 0.44 0.50 0.44 0.61 0.56 0.62 0.7234 0.32 0.44 0.35 0.42 0.63 0.90 Tianjin 0.20 0.51 0.27 0.68 Mean 0.8235 0.17 0.53 0.28 0.47 0.36 0.65 Beijing 0.36 0.53 0.26 0.52 Mean 0.44 0.65 36 0.15 0.57 0.30 0.48 0.60 0.55 Naning 0.18 0.61 0.35 Mean 0.47 0.75 0.6337 0.52 0.53 0.69 0.64 0.75 0.60 Lanzhou 0.40 0.65 Mean 0.69 0.47 0.79 0.6738 0.42 0.77 0.81 0.43 0.81 0.74 Mean Xi’an 0.50 0.72 0.86 0.56 1.00 0.62 1.0339 1.20 0.81 0.51 0.84 0.55 0.88 Zhengzhou 1.02 1.10 0.82 0.51 0.8840 Mean Mean 0.75 0.83 0.70 0.43 0.81 Chengdu 0.87 0.86 0.60 0.83 0.68 0.41 0.6841 1.04 1.07 0.67 0.64 0.62 Mean 0.56 Hangzhou 1.00 1.02 0.91 0.63 0.56 1.09 0.59 0.9142 0.81 Mean 0.79 0.63 1.24 0.63 0.90 Pudong 0.83 1.08 1.04 0.58 1.30 0.68 1.0843 0.81 1.15 0.63 1.07 0.78 1.00 Hefei Mean 0.97 1.23 0.74 0.87 0.9344 1.14 0.50 1.17 1.03 0.88 1.13 Kuming 0.97 0.90 0.86 0.94 0.89 0.9145 Mean 0.67 0.83 1.02 1.20 0.74 Panyu 0.81 0.97 0.80 Mean 0.78 0.74 0.70 46 0.89 1.04 0.77 0.20 0.84 0.50 Nanjing 1.03 1.26 0.19 1.02 0.79 Mean47 0.71 0.90 0.62 1.08 1.16 0.77 Shenyang 0.92 0.81 0.48 Mean 0.95 1.0848 1.15 0.63 0.49 0.73 0.98 Mean 1.22 Anshan 0.72 0.69 0.45 0.72 0.9849 0.59 0.60 0.46 1.01 0.67 Benxi 0.75 0.65 Mean 0.78 0.84 0.6050 1.07 0.76 0.56 0.65 0.85 0.46 Fushun 0.71 0.80 0.75 0.25 0.98 0.53 0.78 Mean 0.44 0.15 1.19 0.91 0.89 0.78 0.16 1.55 Mean 0.86 0.90 1.08 0.64 0.60 0.66 1.01 0.80 0.60 0.26 1.03 0.58 0.66 0.92 0.82 0.81 0.61 0.72 0.73 0.75 0.54 0.77 0.91 0.49 0.62 0.51 1.12 0.50 0.51 0.57 1.13 0.41 0.43 0.84 0.66 0.82 0.59 0.67 0.45 0.46 0.40 0.55 0.48 1 Akedala2 Lhasa3 Mean 1.45 Mt. Waliguan4 1.23 Mean Mean 0.90 Shangri-La 0.615 0.80 1.00 0.36 0.62 Mean 0.88 Ejina 0.256 0.53 1.16 0.96 0.35 0.73 1.22 1.18 Zhurihe 0.407 0.76 1.20 1.24 0.56 0.85 1.19 1.02 Mean Hami 0.968 0.94 1.09 1.20 Mean 0.73 0.74 1.22 1.27 1.19 Xilinhot 0.56 1.08 0.659 1.16 1.49 1.32 0.35 0.80 0.77 1.07 1.08 Mean Wulate 0.35 0.48 0.7510 1.08 1.34 0.86 0.39 0.42 Mean 0.65 Zhangbei 0.92 1.50 0.51 0.49 0.80 0.6911 1.33 0.39 0.58 0.87 0.74 Mean Jiuquan 1.20 Mean 0.50 0.61 0.87 0.73 0.8612 0.72 0.56 0.68 0.73 0.75 0.62 Dunhuang 0.68 0.48 0.64 0.75 0.78 0.53 Mean13 0.75 0.48 0.73 0.70 0.86 0.48 0.67 Mean Minqin 0.71 0.39 0.72 0.94 0.88 0.92 0.5914 0.65 0.71 0.62 1.15 0.89 0.89 0.40 Tazhong 0.47 0.55 0.76 0.89 0.88 0.3115 0.27 Mean 0.45 0.62 0.76 0.81 0.46 Hotan 0.26 0.62 0.54 0.84 Mean 0.73 0.74 0.5116 0.33 0.66 0.54 0.82 0.61 0.71 0.47 Dongsheng 0.36 0.50 0.36 0.36 0.74 0.4617 0.38 0.35 Mean Mean 0.12 0.84 0.37 Yulin 0.46 0.39 0.87 0.10 0.66 0.4718 0.50 0.44 0.69 0.10 0.18 0.65 Yan’an 0.53 0.51 0.57 0.50 0.11 0.13 0.68 19 0.65 0.53 0.44 0.15 0.07 Mean Mt. 0.65 Gaolan 0.57 0.74 0.17 0.0620 0.98 Mean 0.57 0.91 0.21 0.07 Mean Yushe 0.59 1.04 0.61 0.98 0.36 0.1521 0.59 0.94 0.65 0.66 1.21 0.56 0.08 Changde 0.67 0.77 0.63 0.88 0.57 0.1122 0.54 0.64 0.60 Mean 0.73 0.20 Mt. 0.64 0.57 Longfeng 0.65 Mean 1.05 0.72 0.3923 0.92 0.56 Mean 1.05 1.36 1.04 0.81 0.59 Mt. 1.25 0.84 Tai 1.35 0.97 1.26 0.7824 1.02 0.88 1.37 1.01 0.96 0.76 Dongtan 0.93 0.87 1.38 1.14 0.79 0.8225 0.93 0.79 1.33 0.97 0.93 1.11 Mean Shangdianzi 0.80 0.91 1.26 1.01 1.28 1.20 1.14 Mean 0.86 1.39 Mean 0.91 1.27 1.25 1.06 1.21 0.77 1.49 1.11 1.38 1.20 1.00 0.99 1.43 1.11 1.40 1.04 0.79 1.03 1.42 1.00 1.30 1.02 0.42 1.00 1.42 0.92 1.36 1.01 1.30 1.19 1.42 0.96 0.93 1.14 1.21 1.32 1.17 1.03 1.20 1.19 1.29 1.25 1.05 1.20 1.09 0.98 1.18 1.20 1.02 1.14 1.12 1.34 1.08 Data of Figs. 5–15: Alpha. Continued. Table A4. Table A3. Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 12760 12759 SD 0.20SD 0.28 0.31 0.26SD 0.32 0.30 0.35 0.26 0.37SD 0.21 0.28 0.34 0.16 0.66 0.27 0.32SD 0.17 0.55 0.32 0.31 0.26 0.39 0.30 0.24 0.23SD 0.22 0.38 0.33 0.30 0.23 0.15 0.39 0.43 0.34 0.19 0.33SD 0.32 0.32 0.30 0.27 0.25 0.37 0.33 0.25 0.18 0.26 0.28 0.39SD 0.29 0.28 0.29 0.40 0.32 0.31 0.37 0.21 0.24 0.34 0.32 0.27SD 0.42 0.33 0.20 0.33 0.29 0.33 0.47 0.34 0.25 0.29 0.30 0.30SD 0.64 0.24 0.25 0.25 0.28 0.37 0.26 0.27 0.34 0.24 0.30 0.35SD 0.17 0.25 0.39 0.28 0.33 0.27 0.20 0.24 0.34 0.34 0.22 0.14SD 0.16 0.22 0.37 0.25 0.31 0.14 0.20 0.33 0.25 0.35 0.22 0.27SD 0.22 0.25 0.26 0.23 0.31 0.30 0.29 0.30 0.30 0.22 0.32 0.30SD 0.28 0.28 0.32 0.31 0.29 0.25 0.26 0.32 0.36 0.27 0.56 0.26SD 0.27 0.33 0.33 0.26 0.26 0.26 0.32 0.36 0.23 0.40 0.20 0.34SD 0.32 0.39 0.22 0.27 0.16 0.32 0.35 0.19 0.14 0.14 0.32 0.34SD 0.29 0.19 0.21 0.18 0.35 0.25 0.32 0.23 0.22 0.28 0.21 0.24SD 0.32 0.22 0.20 0.22 0.23 0.22 0.28 0.28 0.20 0.25 0.22 0.30SD 0.27 0.20 0.14 0.27 0.26 0.25 0.23 0.25 0.32 0.28 0.32 0.29SD 0.19 0.28 0.36 0.25 0.23 0.19 0.23 0.16 0.21 0.29 0.05 0.17SD 0.15 0.17 0.18 0.23 0.04 0.18 0.27 0.34 0.52 0.17 0.12 0.27SD 0.38 0.24 0.17 0.33 0.21 0.36 0.25 0.14 0.23 0.18 0.47SD 0.18 0.31 0.17 0.13 0.23 0.40 0.38 0.34 0.43 0.51SD 0.17 0.09 0.26 0.16 0.26 0.45 0.14 0.19 0.24 0.24SD 0.31 0.20 0.11 0.25 0.23 0.28 0.13 0.11 0.15 0.22 0.14 0.25 0.14 0.17 0.30 0.14 0.26 0.27 0.10 0.18 0.22 0.26 0.16 0.32 0.14 0.23 0.20 0.26 0.29 0.27 0.23 0.21 0.18 0.36 0.31 0.21 0.17 0.32 0.23 0.35 0.69 0.23 0.26 0.15 0.26 0.26 0.25 0.17 Site Alpha Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 26 Huimin27 Gucheng Mean28 1.16 Mean Lin’an 1.09 1.3629 0.97 1.23 Tongyu 0.96 1.10 Mean30 0.95 1.16 1.27 Urumqi Mean 1.19 1.06 1.3031 1.92 1.25 1.22 1.13 Datong 1.90 Mean 1.32 1.27 0.9732 1.34 1.08 1.33 1.34 1.18 Yinchuan 1.04 Mean 1.02 1.22 1.26 1.2433 1.05 0.91 0.91 1.26 Mean 1.32 1.26 Dalian 1.21 0.80 0.74 1.03 1.04 1.35 1.4434 1.27 0.68 0.78 0.74 1.22 1.39 Tianjin 1.13 0.63 0.85 0.56 Mean 1.3835 1.08 0.72 1.05 0.58 0.95 1.40 Beijing 1.26 0.86 0.92 Mean 0.85 0.96 1.29 36 1.44 0.94 0.91 0.94 1.07 0.94 Naning 1.55 0.99 0.99 Mean 1.02 1.06 1.0437 0.98 1.13 0.98 0.99 0.93 1.11 Lanzhou 0.84 Mean 1.15 0.94 0.78 0.88 1.2138 0.86 1.62 0.87 0.99 0.96 1.25 Mean Xi’an 0.90 1.64 0.79 0.93 1.15 1.2639 1.03 1.50 0.89 1.00 1.14 1.24 Zhengzhou 0.86 1.43 1.14 1.24 1.3140 Mean 0.65 Mean 1.42 1.10 1.18 1.26 Chengdu 0.58 1.15 0.97 1.22 1.21 1.13 1.04 41 0.70 1.15 0.88 1.37 1.11 1.17 Mean Hangzhou 0.92 0.82 0.73 1.66 1.10 1.08 1.1142 1.02 0.82 0.59 Mean 1.63 1.04 1.04 Pudong 1.01 0.91 0.79 1.34 1.52 0.99 0.9343 1.03 1.18 0.88 1.30 1.59 0.98 Hefei 1.04 1.25 Mean 1.03 1.21 1.45 0.9744 1.11 1.26 1.37 1.15 1.09 1.11 Kuming 1.05 1.24 1.27 0.99 1.22 1.1945 1.25 Mean 1.04 1.00 1.27 1.21 Panyu 1.12 1.30 1.14 Mean 0.83 1.18 1.0546 0.99 1.22 1.19 0.91 1.55 1.29 1.11 Nanjing 0.94 1.23 1.69 1.33 Mean 1.2447 0.89 1.31 1.52 1.38 1.10 1.35 Shenyang 1.14 1.28 Mean 1.32 1.22 1.3748 1.19 1.24 1.14 1.29 Mean 1.08 1.42 Anshan 1.14 1.41 0.98 1.18 1.3049 1.35 1.38 0.90 1.09 1.39 Benxi 1.38 1.26 Mean 1.06 1.01 1.4950 0.48 1.37 0.72 1.00 0.99 1.14 Fushun 0.84 1.13 0.95 1.32 1.27 1.26 0.79 Mean 0.83 1.24 1.35 1.45 0.69 Mean 0.59 1.21 1.34 1.48 0.87 0.29 1.34 0.95 1.32 0.73 0.75 1.37 1.03 0.64 1.34 0.94 0.79 1.34 0.42 1.05 0.66 1.36 0.59 1.11 1.09 0.41 0.20 1.16 1.06 0.53 0.84 1.07 0.88 0.39 0.77 0.87 0.49 0.52 0.72 1.01 0.55 0.81 0.51 0.95 1.03 1.07 Continued. Locations of the 50 CARSNET sites in China. Figure 1. Table A4. Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | : d : fall; and c

140 140 140 140 140 140 : summer; b 130 130 130 130 Mt.Longfeng Mt.Longfeng Mt.Longfeng Mt.Longfeng Fushu Benxi Fushu Benxi Fushu Benxi Fushu Benxi Anshan Shenyang Anshan Shenyang Tongyu Anshan Tongyu Shenyang Tongyu Anshan Shenyang Tongyu Dalian Dalian Dalian Dongtan Dongtan Dongtan Pudong Pudong Pudong Dalian Dongtan Pudong 120 120 120 Lin'an Lin'an Lin'an Hangzhou Hangzhou 120 Hangzhou Lin'an Nanjing Nanjing Hangzhou Nanjing 130 130 Huimin Huimin Huimin Mt.Tai Mt.Tai Tianjin Tianjin Mt.Tai Tianjin Hefei Hefei Huimin Hefei Beijing Mt.Tai Beijing Tianjin Beijing Xilinhot Hefei Shangdianzi Xilinhot Shangdianzi Xilinhot Shangdianzi Beijing Gucheng Gucheng Gucheng Xilinhot Shangdianzi Gucheng Zhangbei Zhangbei Zhangbei Panyu Panyu Zhangbei Panyu Datong Datong Yushe Datong Yushe Yushe Zhengzhou Zhurihe Panyu Zhengzhou Zhurihe Zhengzhou Zhurihe Datong Yushe Zhengzhou Zhurihe Changde Changde Changde Changde 110 110 110 Yanan Yulin Mt.Longfeng Yanan Yulin 110 Yanan Xi'an Yulin Mt.Longfeng Xi'an Xi'an Dongsheng Ulate Yanan Dongsheng Yulin Ulate Dongsheng Ulate Xi'an Dongsheng : spring; Ulate Nanning Nanning Nanning Nanning Yinchuan Yinchuan Yinchuan Yinchuan Fushu Benxi Fushu a Benxi Chengdu Lanzhou Chengdu Lanzhou Chengdu Lanzhou Mt.Gaolan Minqin Mt.Gaolan Minqin Mt.Gaolan Minqin Chengdu Lanzhou Mt.Gaolan Minqin Anshan Kunming Shenyang Tongyu Anshan Kunming Shenyang Kunming Tongyu Ejina Kunming Ejina Ejina Ejina 100 100 100 Dalian Dalian Mt.Waliguan Dongtan 100 Mt.Waliguan Mt.Waliguan Dongtan Pudong Mt.Waliguan Pudong Shangri-La Shangri-La Shangri-La Jiuquan Shangri-La Jiuquan Jiuquan Jiuquan 120 120 Lin'an Lin'an Hangzhou Hangzhou Dunhuang Hami Dunhuang Hami Dunhuang Hami Nanjing Hami Dunhuang Nanjing Lhasa Huimin Lhasa Lhasa Huimin Lhasa 90 Mt.Tai Tianjin Mt.Tai 90 90 Tianjin 90 Hefei : winter) based on CARSNET measure- Hefei Beijing Beijing Xilinhot Shangdianzi Akedala Xilinhot Urumqi Shangdianzi Akedala Akedala Urumqi Akedala Urumqi Urumqi Gucheng Gucheng h Zhangbei Zhangbei Tazhong Tazhong Tazhong Tazhong Panyu Panyu Datong Datong Yushe Yushe Zhengzhou Zhurihe Zhengzhou Zhurihe 80 80 80 80 Hotan Hotan Hotan Hotan 0 to 0.4 0.4 to 0.6 0.6 to 0.8 0.8 to 1 1 to 1.2 1.2 to 2 0 to 0 0.2 to 0.2 0.4 to 0.4 0.6 to 0.6 0.8 to 0.8 1.2 0 to 0.2 to 0 0.4 to 0.2 0.6 to 0.4 0.8 to 0.6 1.2 to 0.8 Changde Changde 0 to 0.4 0.6 0.4 to 0.8 0.6 to 1 0.8 to 1 to 1.2 2 1.2 to Alpha based on CARSNET measurements. (d) Winter-AOD (b) Summer-AOD (i) Winter-Alpha (g) Summer-Alpha 110 110 Yanan Yulin Yanan Yulin Xi'an Xi'an Dongsheng Ulate Dongsheng Ulate 50 40 30 20 50 40 30 20 50 40 30 20 50 40 30 20 Nanning Nanning (b) Yinchuan Yinchuan 140 140 140 140 Chengdu Lanzhou Chengdu Lanzhou Mt.Gaolan Minqin Mt.Gaolan Minqin 12761 12762 Kunming Kunming Ejina Ejina : fall; and 130 100 100 130 130 130 Mt.Waliguan Mt.Waliguan g Shangri-La Shangri-La Mt.Longfeng Jiuquan Mt.Longfeng Jiuquan Mt.Longfeng Mt.Longfeng Fushu Benxi Fushu Benxi Fushu Benxi Fushu Benxi Anshan Shenyang Tongyu Anshan Shenyang Tongyu Anshan Shenyang Tongyu Anshan Shenyang Tongyu Dalian Dongtan Dalian Pudong Dalian Dongtan Dongtan Dalian Pudong Dongtan Pudong Pudong 120 120 Lin'an 120 120 Lin'an Lin'an Hangzhou Lin'an Hangzhou Hangzhou Hangzhou Nanjing Nanjing Nanjing Nanjing Huimin Mt.Tai Huimin Tianjin Huimin Dunhuang Hami Mt.Tai Huimin Tianjin Mt.Tai Dunhuang Hami Tianjin Mt.Tai Hefei Tianjin Hefei Beijing Hefei Hefei Beijing Beijing Beijing Xilinhot Shangdianzi Xilinhot Shangdianzi Xilinhot Shangdianzi Xilinhot Shangdianzi Gucheng Gucheng Gucheng Gucheng Zhangbei Zhangbei Zhangbei AOD and Zhangbei Panyu Panyu Datong Panyu Panyu Datong Yushe Yushe Datong Datong Yushe Yushe Zhengzhou Zhurihe Zhengzhou Zhurihe Zhengzhou Zhurihe Zhengzhou Zhurihe Lhasa Lhasa Changde Changde Changde Changde 90 110 110 90 110 110 Yanan Yanan Yulin Yulin Yanan Yanan Yulin Yulin Xi'an Xi'an Xi'an Xi'an Dongsheng Dongsheng Ulate Ulate Dongsheng Dongsheng Ulate Ulate Nanning Nanning Nanning Nanning Yinchuan Yinchuan Yinchuan Yinchuan Akedala (a) Akedala Urumqi Urumqi Chengdu Lanzhou Chengdu Lanzhou Chengdu Chengdu Lanzhou Lanzhou Mt.Gaolan Minqin Mt.Gaolan Minqin Mt.Gaolan Minqin Mt.Gaolan Minqin Kunming Kunming Kunming Kunming Ejina Ejina Ejina Ejina 100 100 100 100 Mt.Waliguan Mt.Waliguan Mt.Waliguan Mt.Waliguan Shangri-La Shangri-La Shangri-La Shangri-La Jiuquan Jiuquan Jiuquan Jiuquan : summer; Tazhong Tazhong f Hami Dunhuang Dunhuang Hami Hami Dunhuang Hami Dunhuang Lhasa Lhasa Lhasa 90 Lhasa 90 90 90 80 80 Hotan Hotan Akedala Akedala Urumqi Akedala Urumqi Urumqi Akedala Urumqi 0 to 0.2 0 to to 0.4 0.2 to 0.6 0.4 to 0.8 0.6 to 1.2 0.8 (b) Alpha Tazhong Tazhong Tazhong (a) AOD (a) Tazhong 0 to 0.4 to 0 0.6 to 0.4 0.8 to 0.6 1 to 0.8 1.2 to 1 2 to 1.2 80 80 80 Hotan Hotan Hotan 80 Hotan 0 to 0.2 0.2 to 0.4 0.4 to 0.6 0.6 to 0.8 0.8 to 1.2 0 to 0.4 0.4 to 0.6 0.6 to 0.8 0.8 to 1 1 to 1.2 1.2 to 2 0 to 0.2 0.2 to 0.4 0.4 to 0.6 0.6 to 0.8 0.8 to 1.2 0 to 0.4 0 to to 0.6 0.4 to 0.8 0.6 to 1 0.8 1.2 1 to to 2 1.2 (a) Spring-AOD (h) Fall-Alpha (f) Spring-Alpha (c) Fall-AOD 50 40 30 20 50 40 30 20 50 40 30 20 50 40 30 20 50 40 30 20 50 40 30 20 : spring; e Spatial distributions of Seasonally stratified spatial distributions of AOD ( Figure 3. winter) and Alpha ( Figure 2. ments. Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | at remote, rural, and urban (e–h) and Alphas 12764 12763 (a–d) Alphas at remote, rural, and urban regions of China. (b) AODs and Seasonally averaged AODs Figure 5. regions of China. Figure 4. (a) Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 12766 12765 Monthly-averaged Alphas at remote sites. Monthly-averaged AODs at remote sites. Figure 7. Figure 6. Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 12768 12767 Monthly-averaged Alphas at rural desert sites. Monthly-averaged AODs at rural desert sites. Figure 9. Figure 8. Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 12770 12769 Monthly-averaged Alphas at rural Loess Plateau sites. Monthly-averaged AODs at rural Loess Plateau sites. Figure 11. Figure 10. Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 12772 12771 Monthly-averaged Alphas at rural central and eastern China sites. Monthly-averaged AODs at rural central and eastern China sites. Figure 13. Figure 12. Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 12774 12773 Monthly-averaged Alphas at urban sites. Monthly-averaged AODs at urban sites. Figure 15. Figure 14. Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 12776 12775 Temporal variations of AODs from 2002 to 2013 based on 12 long-term sites. Annually-averaged AODs for the 12 long-term CARSNET sites. Figure 17. Figure 16.