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The trajectory data generated by various position-aware devices is widely used in various fields of society, but its conventional vector representation and various analysis algorithms based on it have high computational complexity. This makes it difficult to meet the application requirements of real-time or near real-time management and analysis of large-scale trajectory data. In view of the above challenges, this paper proposes a trajectory data management and analysis technology framework based on the Spatiotemporal Grid Model (STGM). First, the trajectory data is represented by spatiotemporal grid encoding instead of vector coordinates, and it can achieve dimensionality reduction and integrated management of high-dimensional heterogeneous trajectory data. Second, the trajectory computing and analysis methods based on STGM are introduced, which reduce the computing complexity of algorithms. Furthermore, various types of trajectory mining and applications are realized on the basis of high-performance computing technologies. Finally, a trajectory data management and analysis prototype system based on the STGM is developed, and experimental results verify the reliability and effectiveness of the proposed technology framework.

Anthropogenic emissions of air pollutants in China influence not only local and regional environments but also the global atmospheric environment; therefore, it is important to understand how China's air pollutant emissions will change and how they will affect regional air quality in the future. Emission scenarios in 2020 were projected using forecasts of energy consumption and emission control strategies based on emissions in 2005, and on recent development plans for key industries in China. We developed four emission scenarios: REF[0] (current control legislations and implementation status), PC[0] (improvement of energy efficiencies and current environmental legislation), PC[1] (improvement of energy efficiencies and better implementation of environmental legislation), and PC[2] (improvement of energy efficiencies and strict environmental legislation). Under the REF[0] scenario, the emission of SO2, NOx, VOC and NH3 will increase by 17%, 50%, 49% and 18% in 2020, while PM10 emissions will be reduced by 10% over East China, compared to that in 2005. In PC[2], sustainable energy polices will reduce SO2, NOx and PM10 emissions by 4.1 Tg, 2.6 Tg and 1.8 Tg, respectively; better implementation of current control policies will reduce SO2, NOx and PM10 emission by 2.9 Tg, 1.8 Tg, and 1.4 Tg, respectively; strict emission standards will reduce SO2, NOx and PM10 emissions by 3.2 Tg, 3.9 Tg, and 1.7 Tg, respectively. Under the PC[2] scenario, SO2 and PM10 emissions will decrease by 18% and 38%, while NOx and VOC emissions will increase by 3% and 8%, compared to that in 2005. Future air quality in China was simulated using the Community Multi-scale Air Quality Model (CMAQ). Under REF[0] emissions, compared to 2005, the surface concentrations of SO2, NO2, hourly maximum ozone in summer, PM2.5, total sulfur and nitrogen depositions will increase by 28%, 41%, 8%, 8%, 19% and 25%, respectively, over east China. Under the PC[2] emission scenario, the surface concentrations of SO2, PM2.5, total sulfur depositions will decrease by 18%, 16% and 15%, respectively, and the surface concentrations of NO2, nitrate, hourly maximum ozone in summer, total nitrogen depositions will be kept as 2005 level, over east China. The individual impacts of SO2, NOx, NH3, NMVOC and primary PM emission changes on ozone and PM2.5 concentrations have been analyzed using sensitivity analysis. The results suggest that NOx emission control need to be enhanced during the summertime to obtain both ozone and PM2.5 reduction benefits. NH3 emission controls should also be considered in order to reduce both nitrate concentration and total nitrogen deposition in the future.

Based upon 14 field surveys conducted between 2003 and 2008, we showed that the seasonal pattern of sea surface partial pressure of CO2 (pCO2) and sea–air CO2 fluxes differed among four different physical–biogeochemical domains in the South China Sea (SCS) proper. The four domains were located between 7 and 23° N and 110 and 121° E, covering a surface area of 1344 × 103 km2 and accounting for ~ 54% of the SCS proper. In the area off the Pearl River estuary, relatively low pCO2 values of 320 to 390 μatm were observed in all four seasons and both the biological productivity and CO2 uptake were enhanced in summer in the Pearl River plume waters. In the northern SCS slope/basin area, a typical seasonal cycle of relatively high pCO2 in the warm seasons and relatively low pCO2 in the cold seasons was revealed. In the central/southern SCS area, moderately high sea surface pCO2 values of 360 to 425 μatm were observed throughout the year. In the area west of the Luzon Strait, a major exchange pathway between the SCS and the Pacific Ocean, pCO2 was particularly dynamic in winter, when northeast monsoon induced upwelling events and strong outgassing of CO2. These episodic events might have dominated the annual sea–air CO2 flux in this particular area. The estimate of annual sea–air CO2 fluxes showed that most areas of the SCS proper served as weak to moderate sources of the atmospheric CO2, with sea–air CO2 flux values of 0.46 ± 0.43 mol m−2 yr−1 in the northern SCS slope/basin, 1.37 ± 0.55 mol m−2 yr−1 in the central/southern SCS, and 1.21 ± 1.48 mol m−2 yr−1 in the area west of the Luzon Strait. However, the annual sea–air CO2 exchange was nearly in equilibrium (−0.44 ± 0.65 mol m−2 yr−1) in the area off the Pearl River estuary. Overall the four domains contributed (18 ± 10) × 1012 g C yr−1 to the atmospheric CO2.