| 1 | Vertical Distribution Characteristics of PM2.5 Observed by a Mobile Vehicle Lidar in Tianjin, China in 2016显示文摘We present mobile vehicle lidar observations in Tianjin, China during the spring, summer, and winter of 2016. Mobile observations were carried out along the city border road of Tianjin to obtain the vertical distribution characteristics of PM_(2.5). Hygroscopic growth was not considered since relative humidity was less than 60% during the observation experiments. PM_(2.5) profile was obtained with the linear regression equation between the particle extinction coefficient and PM_(2.5) mass concentration. In spring, the vertical distribution of PM_(2.5) exhibited a hierarchical structure. In addition to a layer of particles that gathered near the ground, a portion of particles floated at 0.6–2.5-km height. In summer and winter, the fine particles basically gathered below 1 km near the ground. In spring and summer, the concentration of fine particles in the south was higher than that in the north because of the influence of south wind. In winter, the distribution of fine particles was opposite to that measured during spring and summer. High concentrations of PM_(2.5) were observed in the rural areas of North Tianjin with a maximum of 350 μg m–3 on 13 December2016. It is shown that industrial and ship emissions in spring and summer and coal combustion in winter were the major sources of fine particles that polluted Tianjin. The results provide insights into the mechanisms of haze formation and the effects of meteorological conditions during haze–fog pollution episodes in the Tianjin area. | Lihui LYU Yunsheng DONG Tianshu ZHANG Cheng LIU Wenqing LIU Zhouqing XIE Yan XIANG Yi ZHANG Zhenyi CHEN Guangqiang FAN Leibo ZHANG Yang LIU Yuchen SHI Xiaowen SHU | 2018 | Journal of Meteorological Research2018，32，1： | 5 |
| 2 | Simulated effect of soil freeze-thaw process on surface hydrologic and thermal fluxes in frozen ground region of the Northern Hemisphere显示文摘Soil freeze-thaw process is closely related to surface energy budget,hydrological activity,and terrestrial ecosystems.In this study,two numerical experiments(including and excluding soil freeze-thaw process)were designed to examine the effect of soil freeze-thaw process on surface hydrologic and thermal fluxes in frozen ground region in the Northern Hemisphere based on the state-of-the-art Community Earth System Model version 1.0.5.Results show that in response to soil freeze-thaw process,the area averaged soil temperature in the shallow layer(0.0175−0.0451 m)decreases by 0.35℃in the TP(Tibetan Plateau),0.69℃in CES(Central and Eastern Siberia),and 0.6℃in NA(North America)during summer,and increases by 1.93℃in the TP,2.28℃in CES and 1.61℃in NA during winter,respectively.Meanwhile,in response to soil freeze-thaw process,the area averaged soil liquid water content increases in summer and decrease in winter.For surface heat flux components,the ground heat flux is most significantly affected by the freeze-thaw process in both summer and winter,followed by sensible heat flux and latent heat flux in summer.In the TP area,the ground heat flux increases by 2.82 W/m2(28.5%)in summer and decreases by 3.63 W/m2(40%)in winter.Meanwhile,in CES,the ground heat flux increases by 1.89 W/m2(11.3%)in summer and decreases by 1.41 W/m2(18.6%)in winter.The heat fluxes in the Tibetan Plateau are more susceptible to the freeze-thaw process compared with the high-latitude frozen soil regions.Soil freeze-thaw process can induce significant warming in the Tibetan Plateau in winter.Also,this process induces significant cooling in high-latitude regions in summer.The frozen ground can prevent soil liquid water from infiltrating to deep soil layers at the beginning of thawing;however,as the frozen ground thaws continuously,the infiltration of the liquid water increases and the deep soil can store water like a sponge,accompanied by decreasing surface runoff.The influence of the soil freeze-thaw process on surface hydrologic and thermal fluxes varies seasonally and spatially. | Di Ma SiQiong Luo DongLin Guo ShiHua Lyu XianHong Meng BoLi Chen LiHui Luo | 2021 | Research in Cold and Arid Regions2021，13，1： | 4 |
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