Abstract. In 2013, China's government published the Air Pollution Prevention and Control Action Plan (APPCAP) with a specific target for Beijing, which aims to reduce annual mean PM2.5 concentrations in Beijing to 60 µg m−3 in 2017. During 2013–2017, the air quality in Beijing was significantly improved following the implementation of various emission control measures locally and regionally, with the annual mean PM2.5 concentration decreasing from 89.5 µg m−3 in 2013 to 58 µg m−3 in 2017. As meteorological conditions were more favourable to the reduction of air pollution in 2017 than in 2013 and 2016, the real effectiveness of emission control measures on the improvement of air quality in Beijing has frequently been questioned. In this work, by combining a detailed bottom-up emission inventory over Beijing, the MEIC regional emission inventory and the WRF-CMAQ (Weather Research and Forecasting Model and Community Multiscale Air Quality) model, we attribute the improvement in Beijing's PM2.5 air quality in 2017 (compared to 2013 and 2016) to the following factors: changes in meteorological conditions, reduction of emissions from surrounding regions, and seven specific categories of local emission control measures in Beijing. We collect and summarize data related to 32 detailed control measures implemented during 2013–2017, quantify the emission reductions associated with each measure using the bottom-up local emission inventory in 2013, aggregate the measures into seven categories, and conduct a series of CMAQ simulations to quantify the contribution of different factors to the PM2.5 changes. We found that, although changes in meteorological conditions partly explain the improved PM2.5 air quality in Beijing in 2017 compared to 2013 (3.8 µg m−3, 12.1 % of total), the rapid decrease in PM2.5 concentrations in Beijing during 2013–2017 was dominated by local (20.6 µg m−3, 65.4 %) and regional (7.1 µg m−3, 22.5 %) emission reductions. The seven categories of emission control measures, i.e. coal-fired boiler control, clean fuels in the residential sector, optimize industrial structure, fugitive dust control, vehicle emission control, improved end-of-pipe control, and integrated treatment of VOCs, reduced the PM2.5 concentrations in Beijing by 5.9, 5.3, 3.2, 2.3, 1.9, 1.8, and 0.2 µg m−3, respectively, during 2013–2017. We also found that changes in meteorological conditions could explain roughly 30 % of total reduction in PM2.5 concentration during 2016–2017 with more prominent contribution in winter months (November and December). If the meteorological conditions in 2017 had remained the same as those in 2016, the annual mean PM2.5 concentrations would have increased from 58 to 63 µg m−3, exceeding the target established in the APPCAP. Despite the remarkable impacts from meteorological condition changes, local and regional emission reductions still played major roles in the PM2.5 decrease in Beijing during 2016–2017, and clean fuels in the residential sector, coal-fired boiler control, and optimize industrial structure were the three most effective local measures (contributing reductions of 2.1, 1.9, and 1.5 µg m−3, respectively). Our study confirms the effectiveness of clean air actions in Beijing and its surrounding regions and reveals that a new generation of control measures and strengthened regional joint emission control measures should be implemented for continued air quality improvement in Beijing because the major emitting sources have changed since the implementation of the clean air actions.

Abstract. Four extreme haze episodes occurred in October 2014 in the North China Plain (NCP). To clarify the formation mechanism of hazes in autumn, strengthened observations were conducted in Beijing from 5 October to 2 November. The meteorological parameters, satellite data, chemical compositions and optical properties of aerosols were obtained. The hazes originated from the NCP, developing in the southwest and northeast directions, with the highest concentration of PM2.5 of 469 μg m−3 in Beijing. The NCP was dominated by a weak high pressure system during the haze episode, which resulted in low surface wind speed and relatively stagnant weather. Moreover, the wind slowed down around Beijing city. The secondary aerosols NO3− was always higher than that of SO42−, which indicated the motor vehicles played a more important part in the hazes in October 2014, even though the oxidation rate from SO2 to SO42− was faster than that of NOx to NO3−. Sudden increases of the concentrations of organic matter, Cl− and BC (black carbon) before each haze episode implied that regional transport of pollutants by biomass burning was important for haze formation during autumn. A satellite map of fire points and the backward trajectories of the air masses also indicated this pollution source. The distinct decrease in the PBL (planetary boundary layer) height during four haze episodes restrained the vertical dispersion of the air pollutants. Water vapor also played a vital role in the formation of hazes by accelerating the chemical transformation of secondary pollutants, leading to hygroscopic growth of aerosols and altering the thermal balance of the atmosphere.

Due to the cognitive limitations of the human operator and lack of complete information about the remote environment, the work performance of such teleoperation systems cannot be guaranteed in most cases. However, some practical tasks conducted by the teleoperation system require high performances, such as tele-surgery needs satisfactory high speed and more precision control results to guarantee patient' health status. To obtain some satisfactory performances, the error constrained control is employed by applying the barrier Lyapunov function (BLF). With the constrained synchronization errors, some high performances, such as, high convergence speed, small overshoot, and an arbitrarily predefined small residual constrained synchronization error can be achieved simultaneously. Nevertheless, like many classical control schemes only the asymptotic/exponential convergence, i.e., the synchronization errors converge to zero as time goes infinity can be achieved with the error constrained control. It is clear that finite time convergence is more desirable. To obtain a finite-time synchronization performance, the terminal sliding mode (TSM)-based finite time control method is developed for teleoperation system with position error constrained in this paper. First, a new nonsingular fast terminal sliding mode (NFTSM) surface with new transformed synchronization errors is proposed. Second, adaptive neural network system is applied for dealing with the system uncertainties and the external disturbances. Third, the BLF is applied to prove the stability and the nonviolation of the synchronization errors constraints. Finally, some comparisons are conducted in simulation and experiment results are also presented to show the effectiveness of the proposed method.

The master-slave control design problem is considered for networked teleoperation system with friction and external disturbances. A new finite-time synchronization control method is proposed with the help of adaptive fuzzy approximation. We develop a new nonsingular fast terminal sliding mode (NFTSM) to provide faster convergence and higher precision than the linear hyperplane sliding mode and the classic terminal sliding mode (TSM). Then, the adaptive fuzzy-logic system is employed to approximate the system uncertainties and the corresponding adaptive fuzzy NFTSM controller is designed. By constructing Lyapunov function, the stability and finite time synchronization performance are proved with the new controller in the presence of system uncertainties and external disturbances. Compared with the traditional teleoperation design method, the new control scheme achieves better transient-state performance and steady-state performance. Finally, the simulations are performed and the comparisons are shown among the proposed method, the P+d method, the PD+d method, the DFF method and the classic TSM, FTSM. The simulation results further demonstrate the effectiveness of the proposed method.