Based on online observations of fine particulate matter(PM2.5) for five consecutive years from January 2013 to December 2017 in Beijing, combined with simultaneous measurement of gaseous precursors and meteorological ...Based on online observations of fine particulate matter(PM2.5) for five consecutive years from January 2013 to December 2017 in Beijing, combined with simultaneous measurement of gaseous precursors and meteorological parameters, the evolution and meteorological causes of fineparticle explosive growth(FPEG) events were analyzed. During the 5-year observation period,132 FPEG events were observed and these events were further divided into three types(3-, 6-, and 9-h events) according to their evolution duration. The majority of FPEG events were observed in winter under the conditions of higher gas precursor concentrations and unfavorable meteorological conditions. The average concentration of PM2.5 during winter FPEG events changed little from 2013 to 2016, whereas it decreased significantly in 2017, in accordance with the similar variation of gaseous species(SO2, NO2, and CO). In addition, the higher wind speeds and lowest relative humidity observed in 2017 were also conducive to the decrease in PM2.5. The evolutions of FPEG events and normal haze episodes were analyzed, revealing that the rate of increase in NO2 was much greater than that of SO2, suggesting more of a contribution from mobile sources than stationary sources. The polar Plot results suggest that the transportation from the southeast area of Beijing plays a major role in the formation of 3-h events, whereas local emissions is the main contributory factor for 9-h events and normal haze episodes. However, further quantitative analysis regarding the contributions of these factors is still needed.展开更多
In this work, we propose a new model of evolution networks, which is based on the evolution of the traffic flow. In our method, the network growth does not take into account preferential attachment, and the attachment...In this work, we propose a new model of evolution networks, which is based on the evolution of the traffic flow. In our method, the network growth does not take into account preferential attachment, and the attachment of new node is independent of the degree of nodes. Our aim is that employing the theory of evolution network, we give a further understanding about the dynamical evolution of the traffic flow. We investigate the probability distributions and scaling properties of the proposed model The simulation results indicate that in the proposed model, the distribution of the output connections can be well described by scale-free distribution. Moreover, the distribution of the connections is largely related to the traffic flow states, such as the exponential distribution （i.e., the scale-free distribution） and random distribution etc.展开更多
基金This study was supported by The Ministry of Science and Technology of the people's Republic of China:[Grant Numbers 2017YFC0210000 and 2016YFC0202700]the National Natural Science Foundation of China:[Grant Number 41705110].
文摘Based on online observations of fine particulate matter(PM2.5) for five consecutive years from January 2013 to December 2017 in Beijing, combined with simultaneous measurement of gaseous precursors and meteorological parameters, the evolution and meteorological causes of fineparticle explosive growth(FPEG) events were analyzed. During the 5-year observation period,132 FPEG events were observed and these events were further divided into three types(3-, 6-, and 9-h events) according to their evolution duration. The majority of FPEG events were observed in winter under the conditions of higher gas precursor concentrations and unfavorable meteorological conditions. The average concentration of PM2.5 during winter FPEG events changed little from 2013 to 2016, whereas it decreased significantly in 2017, in accordance with the similar variation of gaseous species(SO2, NO2, and CO). In addition, the higher wind speeds and lowest relative humidity observed in 2017 were also conducive to the decrease in PM2.5. The evolutions of FPEG events and normal haze episodes were analyzed, revealing that the rate of increase in NO2 was much greater than that of SO2, suggesting more of a contribution from mobile sources than stationary sources. The polar Plot results suggest that the transportation from the southeast area of Beijing plays a major role in the formation of 3-h events, whereas local emissions is the main contributory factor for 9-h events and normal haze episodes. However, further quantitative analysis regarding the contributions of these factors is still needed.
基金The project supported by National Natural Science Foundations of China under Grant Nos and Technology Foundation of Beijing Jiaotong University under Grant No. 2004SM026 70471088 and 70225005 and Che Science.
文摘In this work, we propose a new model of evolution networks, which is based on the evolution of the traffic flow. In our method, the network growth does not take into account preferential attachment, and the attachment of new node is independent of the degree of nodes. Our aim is that employing the theory of evolution network, we give a further understanding about the dynamical evolution of the traffic flow. We investigate the probability distributions and scaling properties of the proposed model The simulation results indicate that in the proposed model, the distribution of the output connections can be well described by scale-free distribution. Moreover, the distribution of the connections is largely related to the traffic flow states, such as the exponential distribution （i.e., the scale-free distribution） and random distribution etc.
