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Abstract. From 2006 to 2007, the daily concentrations of major inorganic water-soluble constituents, mineral aerosol, organic carbon (OC) and elemental carbon (EC) in ambient PM 10 samples were investigated from 16 urban, rural and remote sites in various regions of China, and were compared with global aerosol measurements. A large difference between urban and rural chemical species was found, normally with 1.5 to 2.5 factors higher in urban than in rural sites. Optically-scattering aerosols, such as sulfate (∼16 %), OC (∼15 %), nitrate (∼7 %), ammonium (∼5 %) and mineral aerosol (∼35 %) in most circumstance, are majorities of the total aerosols, indicating a dominant scattering feature of aerosols in China. Of the total OC, ∼55 %-60 % can be attributed to the formation of the secondary organic carbon (SOC). The absorbing aerosol EC only accounts for ∼3.5 % of the total PM 10 . Seasonally, maximum concentrations of most aerosol species were found in winter while mineral aerosol peaks in spring. In addition to the regular seasonal maximum, secondary peaks were found for sulfate and ammonium in summer and for OC and EC

[1] The elemental (EC) and organic carbon (OC) fractions of ambient aerosols were determined by thermo-chemical analysis of 24-h samples collected during 2006 at 18 stations in China located at various rural, urban and remote locations. The annual mean concentration levels are found to be 0.35 ± 0.01 mg EC m À3 and 3.0 ± 0.21 mg OC m À3 for the remote background sites; 3.6 ± 0.93 mg EC m À3 and 16.1 ± 5.2 mg OC m À3 for the regional sites; and 11.2 ± 2.0 mg EC m À3 and 33.1 ± 9.6 mg OC m À3 for the urban sites, respectively. At rural sites representing regionally dispersed aerosols, levels are comparable to other locations in Asia. At all sites, both EC and OC show a consistent seasonal variation with a peak in winter, dropping in spring, reaching a minimum in summer and then increasing in autumn. The ratio of OC to EC is on the order of 3 for the urban locations, but can reach as high as 6 at the rural sites. This may partly be due to the open biomass burning in field of rural area, but may also indicate the presence of a regional background of secondary organic carbon (SOC) in China. These high ratios of OC/EC complicate the assessment of the climatic impacts of carbonaceous aerosols in China, as optical scattering from the high OC concentrations may lead to a cooling effect that counteracts the possible warming caused by EC optical absorption.

The spatial distribution of the aerosols over 86 Chinese cities was reconstructed from air pollution index (API) records for summer 2000 to winter 2006. PM₁₀ (particulate matter ≤10 μm) mass concentrations were calculated for days when PM₁₀ was the principal pollutant, these accounted for 91.6% of the total 150 428 recorded days. The 83 cities in mid-eastern China (100° E to 130° E) were separated into three latitudinal zones using natural landscape features as boundaries. Areas with high PM₁₀ level in northern China (127 to 192 μg m⁻³) included Urumchi, Lanzhou-Xining, Weinan-Xi'an, Taiyuan-Datong-Yangquan-Changzhi, Pingdingshan-Kaifeng, Beijing-Tianjin-Shijiazhuang, Jinan, and Shenyang-Anshan-Fushun; in the middle zone, high PM₁₀ (119–147 μg m⁻³) occurred at Chongqing-Chengdu-Luzhou, Changsha-Wuhan, and Nanjing-Hangzhou; in the southern zone, only four cities (Qujing, Guiyang, Guangzhou and Shaoguan) showed PM₁₀ concentration >80 μg m⁻³. The median PM₁₀ concentration decreased from 108 μg m⁻³ for the northern cities to 95 μg m⁻³ and 55 μg m⁻³ for the middle and southern zones, respectively. PM₁₀ concentration and the APIs both exhibited wintertime maxima, summertime minima, and the second highest values in spring. PM₁₀showed evidence for a decreasing trend for the northern cities while in the other zones urban PM₁₀ levels fluctuated, but showed no obvious change over time. The spatial distribution of PM₁₀ was compared with the emissions, and the relationship between the surface PM₁₀ concentration and the aerosol optical depth (AOD) was also discussed

Abstract. Concentrations of PM 10 , PM 2.5 and PM 1 were monitored at 24 CAWNET (China Atmosphere Watch Network) stations from 2006 to 2014. The highest particulate matter (PM) concentrations were observed at the stations of Xian, Zhengzhou and Gucheng, on the Guanzhong Plain and the Huabei Plain (HBP). The second highest PM concentrations were observed in northeast China, followed by southern China. According to the latest air quality standards of China, 14 stations reached the PM 10 standard, and only 7 stations, mainly rural and remote stations, reached the PM 2.5 standard. The ratios of PM 2.5 to PM 10 showed a clear increasing trend from northern to southern China, because of the substantial contribution of coarse mineral aerosol in northern China. The ratios of PM 1 to PM 2.5 were higher than 80 % at most stations. PM concentrations tended to be highest in winter and lowest in summer at most stations, and mineral dust influenced the results in spring. A decreasing interannual trend was observed on the HBP and in southern China for the period 2006 to 2014, but an increasing trend occurred at some stations in northeast China. Bimodal and unimodal diurnal variation patterns were identified at urban stations. Both emissions and meteorological variations dominate the long-term PM concentration trend, while meteorological factors play a leading role in the short term.

Abstract. Since there have been individual reports of persistent haze-fog events in January 2013 in central-eastern China, questions on factors causing the drastic differences in changes in 2013 from changes in adjacent years have been raised. Changes in major chemical components of aerosol particles over the years also remain unclear. The extent of meteorological factors contributing to such changes is yet to be determined. The study intends to present the changes in daily based major water-soluble constituents, carbonaceous species, and mineral aerosol in PM 10 at 13 stations within different haze regions in China from 2006 to 2013, which are associated with specific meteorological conditions that are highly related to aerosol pollution (parameterized as an index called Parameter Linking Aerosol Pollution and Meteorological Elements -PLAM). No obvious changes were found in annual mean concentrations of these various chemical components and PM 10 in 2013, relative to 2012. By contrast, wintertime mass of these components was quite different. In Hua Bei Plain (HBP), sulfate, organic carbon (OC), nitrate, ammonium, element carbon (EC), and mineral dust concentrations in winter were approximately 43, 55, 28, 23, 21, and 130 µg m −3 , respectively; these masses were approximately 2 to 4 times higher than those in background mass, which also exhibited a decline during 2006 to 2010 and then a rise till 2013. The mass of these concentrations and PM 10 , except minerals, respectively, increased by approximately 28 to 117 % and 25 % in January 2013 compared with that in January 2012. Thus, persistent haze-fog events occurred in January 2013, and approximately 60 % of this increase in component concentrations from 2012 to 2013 can be attributed to severe meteorological conditions in the winter of 2013. In the Yangtze River Delta (YRD) area, winter masses of these components, unlike HBP, have not significantly increase since 2010; PLAM were also maintained at a similar level without significant changes. In the Pearl River Delta (PRD) area, the regional background concentrations of the major chemical components were similar to those in the YRD, accounting for approximately 60-80 % of those in HBP. Since 2010, a decline has been found for winter concentrations, which can be partially attributable to persistently improving meteorological conditions and emission cutting with an emphasis on coal combustion in this area.

Abstract. The spatial-temporal distributions and sources of sand and dust storm (SDS) in East Asia from 2001 to 2006 were investigated on the basis of visibility and PM 10 data from the routine SDS and weather monitoring networks run by CMA (China Meteorological Administration). A power functional relationships between PM 10 and visibility was found among various regions generally with a good correlation (r 2 =0.90), especially in Asian SDS source regions. In addition, three SDS occurrence centers, i.e. western China, Mongolia and northern China, were identified with the Mongolia source contributing more dust to the downwind areas including Korea and Japan than other two sources. Generally, high PM 10 concentrations were observed in most areas of northern China. The highest value was obtained in the center of western China with a spring daily mean value of 876 µgm −3 , and the value in other source regions exceeds 200 µgm −3 . These data sets together with the satellite observations in China form the main observation database for the evaluation and data assimilation of CUACE/Dust system -an operational SDS forecasting system for East Asia.

Abstract. CUACE/Dust, an operational mesoscale sand and dust storm (SDS) forecasting system for East Asia, has been developed by online coupling a dust aerosol emission scheme and dust aerosol microphysics onto a regional meteorological model with improved advection and diffusion schemes and a detailed Northeast Asia soil erosion database. With improved initial dust aerosol conditions through a 3-DVar data assimilation system, CUACE/Dust successfully forecasted most of the 31 SDS processes in East Asia. A detailed comparison of the model predictions for the 8-12 March SDS process with surface network observations and lidar measurements revealed a robust forecasting ability of the system. The time series of the operationally forecasted dust concentrations for a number of representative stations for the whole spring 2006 (1 March-31 May) were evaluated against surface PM10 monitoring data, showing a good agreement in terms of the SDS timing and magnitudes at and near the source regions where dust aerosols dominate. For the operational forecasts of spring 2006 in East Asia, a TS (threat score) system evaluated the performance of CUACE/Dust against all available observations and rendered a spring averaged TS value of 0.31 for FT1 (24 h forecasts), 0.23 for FT2 (48 h forecasts) and 0.21 for FT3 (72 h forecasts).