Abstract. We investigated aerosol hygroscopic growth property and its influence on scattering coefficient using M9003 nephelometers in coupling with humidity controlled inlet system at a rural site near Beijing mega-city from 24 April to 15 May 2006. Inlet relative humidity was controlled in an increasing range of 40%-90% while aerosol hygroscopic growth factor of scattering coefficient, f (RH=80%) as ratio of scattering coefficient at RH=80% to "dry" scattering coefficient (RH<40%) varied in a range of 1.07-2.35 during the measurement. Further analysis indicated that under dust episode, measured f (RH=80%) is 1.2±0.02, and estimated periodic mean value of f (RH=80%) was 1.31±0.03 under clean periods; during urban pollution periods, the aerosol displayed relative strong water absorbing properties with f (RH=80%) of about 1.57±0.02. An examination of chemical composition of daily filter samples highlighted that aerosol hygroscopicity was generally depressed with the increasing ratio of organic matter (OMC)/ammonium sulfate (AS) in particle mass, similar with the results of many previous studies. However, a special case with high value of f (RH=80%)=2.21 and high OMC/AS ratio was also observed, this exception reflected physico-chemical particularities of organic matter and its complex interaction with other compounds during this episode.

Abstract. An online air pollutant tagged module has been developed in the Nested Air Quality Prediction Model System (NAQPMS) to investigate the impact of local and regional sources on the air pollutants in Beijing during the Campaign of Air Quality Research in Beijing 2006(CAREBeijing-2006). The NAQPMS model shows high performance in simulating sulfur dioxide (SO 2 ), particulate matter (PM 10 ), nitrogen dioxide (NO 2 ), and ozone (O 3 ) with overall better agreements with the observations at urban sites than rural areas. With the tagged module, the air pollutant contributions from local and regional sources to the surface layer (about 30 m) and the upper layer (about 1.1 km) in Beijing are differentiated and estimated. The air pollutants at the surface layer in Beijing are dominated by the contributions from local sources, accounting for 65 % of SO 2 , 75 % of PM 10 and nearly 90 % of NO 2 , respectively, comparatively, the 1.1 km layer has large source contributions from the surrounding regions (e.g., southern Beijing), accounting for more than 50 % of the SO 2 and PM 10 concentrations. County scale analysis is also performed and the results suggest that Tianjin is the dominant source of SO 2 in Pinggu County, and Langfang, Hebei is the most important regional contributor to PM 10 in Beijing. Moreover, the surrounding regions show larger impact on SO 2 , PM 10 and NO 2 in the eastern counties of Beijing (e.g., Pinggu, Tongzhou and Daxing) than those in western Beijing, which is likely due to the Beijing's semi-basin topography and the summer monsoon. Our results indicate that the efforts to control the air pollutants in Beijing should focus on controlling both local and regional emissions.

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Abstract. In order to improve the surface ozone forecast over Beijing and surrounding regions, data assimilation method integrated into a high-resolution regional air quality model and a regional air quality monitoring network are employed. Several advanced data assimilation strategies based on ensemble Kalman filter are designed to adjust O 3 initial conditions, NO x initial conditions and emissions, VOCs initial conditions and emissions separately or jointly through assimilating ozone observations. As a result, adjusting precursor initial conditions demonstrates potential improvement of the 1-h ozone forecast almost as great as shown by adjusting precursor emissions. Nevertheless, either adjusting precursor initial conditions or emissions show deficiency in improving the short-term ozone forecast at suburban areas. Adjusting ozone initial values brings significant improvement to the 1-h ozone forecast, and its limitations lie in the difficulty in improving the 1-h forecast at some urban site. A simultaneous adjustment of the above five variables is found to be able to reduce these limitations and display an overall better performance in improving both the 1-h and 24-h ozone forecast over these areas. The root mean square errors of 1-h ozone forecast at urban sites and suburban sites decrease by 51 % and 58 % respectively compared with those in free run. Through these experiments, we found that assimilating local ozone observations is determinant for ozone forecast over the observational area, while assimilating remote ozone observations could reduce the uncertainty in regional transport ozone.

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Recent studies on regional haze pollution over China come up in general with strong variability of main causes of heavy polluted episodes, in linkage with local specificities, sources and pollution characteristics. This paper therefore aims at elucidating the main specific sources and formation mechanisms of observed strong haze pollution episodes over 1-15 November 2015 in Northeast region considered as one of biggest megacity clusters in China. The Northeast China mega-city cluster, including Heilong Jiang, Jilin and Liaoning provinces, is adjacent to Russia in the north, Mongolian at the west, North Korea at east, and representing key geographical location in the regional and transnational air pollution issues in China due to the presence of heavy industries and intense economic activities. The present study, based on air quality monitoring, remote sensing satellite data and sensitivity experiments carried on the Nested Air Quality Prediction Modeling System (NAQPMS), quantitatively assesses the impact of meteorological conditions and potential contributions from regional chemical transport, intensive energy combustion, illegal emission and biomass burning emissions to PM concentration variation. The results indicate strong inversion occurrence at lower atmosphere with weak near-surface wind speed and high relative humidity, leading to PM concentration increase of about 30-50%. Intensive energy combustion (plausibly for heating activities) and illegal emission also significantly enhance the overall PM accumulation by 100-200 μg m (60-70% increase), against 75-100 μg m from the biomass burning under the northeast-southwest transport pathway, corresponding to a contribution of 10-20% to PM concentration increase. Obviously, stagnant meteorological conditions, energy combustion, illegal emission and biomass burning are main drivers of strong haze formation and spatial distribution over Northeast China megacity cluster. In clear, much effort on emission abatement at both local and regional scales is still an urgent imperative to overcome current critical haze pollution.

Abstract. Predicting air pollution events in the low atmosphere over megacities requires a thorough understanding of the tropospheric dynamics and chemical processes, involving, notably, continuous and accurate determination of the boundary layer height (BLH). Through intensive observations experimented over Beijing (China) and an exhaustive evaluation of existing algorithms applied to the BLH determination, persistent critical limitations are noticed, in particular during polluted episodes. Basically, under weak thermal convection with high aerosol loading, none of the retrieval algorithms is able to fully capture the diurnal cycle of the BLH due to insufficient vertical mixing of pollutants in the boundary layer associated with the impact of gravity waves on the tropospheric structure. Consequently, a new approach based on gravity wave theory (the cubic root gradient method: CRGM) is developed to overcome such weakness and accurately reproduce the fluctuations of the BLH under various atmospheric pollution conditions. Comprehensive evaluation of CRGM highlights its high performance in determining BLH from lidar. In comparison with the existing retrieval algorithms, CRGM potentially reduces related computational uncertainties and errors from BLH determination (strong increase of correlation coefficient from 0.44 to 0.91 and significant decreases of the root mean square error from 643 to 142 m). Such a newly developed technique is undoubtedly expected to contribute to improving the accuracy of air quality modeling and forecasting systems.