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Analysis of air quality characteristics of beijing–tianjin–hebei and its surrounding air pollution transport channel cities in China

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Journal of Environmental Sciences 2020年第1期32卷 213-227页

作者： Cuicui Xiao Miao Chang Peikun Guo Meifeng Gu Yang Li School of Environment Tsinghua University

beijing–tianjin–hebei(BTH)and its surrounding areas are very important to air pollution control in *** analyze the characteristics of BTH and its surrounding areas of China,we collected 5,641,440 air quality data from 161 air monitoring stations and 37,123,000 continuous monitoring data from air polluting enterprises in BTH and surrounding cities to establish an indicator system for urban air quality *** results showed that particulate matter with aerodynamic diameters ofbeijing had the highest air quality population exposure,and that exposure levels in Zhengzhou,Puyang,Anyang,Jincheng were higher than the average of the 31 investigated ***,multiple linear regression revealed a negative correlation between meteorological factors(especially wind and precipitation)and air quality,while a positive correlation existed between industrial pollution emissions and air quality in most of BTH and its surrounding cities.

关键词： beijing–tianjin–hebei Air quality population exposure Seasonal index Hourly change Industrial pollution source emission Meteorology factors

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Comparison of mixing layer height inversion algorithms using lidar and a pollution case study in Baoding, China

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Journal of Environmental Sciences 2019年第5期31卷 81-90页

作者： Xiangguang Ji Cheng Liu Zhouqing Xie Qihou Hu Yunsheng Dong Guangqiang Fan Tianshu Zhang Chengzhi Xing Zhuang Wang Zeeshan Javed Jianguo Liu School of Environmental Science and Optoelectronic Technology University of Science and Technology of China Key Lab of Environmental Optics and Technology Anhui Institute of Optics and Fine Mechanics Hefei Institutes of Physical Science Chinese Academy of Sciences School of Earth and Space Sciences University of Science and Technology of China Center for Excellence in Regional Atmospheric Environment Institute of Urban Environment Chinese Academy of Sciences Anhui Province Key Laboratory of Polar Environment and Global Change University of Science and Technology of China

beijing–tianjin–hebei area is suffering from atmospheric pollution from a long time. The understanding of the air pollution mechanism is of great importance for officials to design strategies for the environmental governance. Mixing layer height(MLH) is a key factor influencing the diffusion of air pollutants. It plays an important role on the evolution of heavy pollution events. Light detection and ranging(lidar), is an effective remote-sensing tool, which can retrieve high spatial and temporal evolution process within mixing layer(ML), especially the variation of MLH. There are many methods to retrieve MLH, but each method has its own applicable limitations. The Mie-lidar data in beijing was firstly used to compare three different algorithms which are widely used under different pollution *** find that the multi-layer structure near surface may cause errors in the detection of mixing layer. The MLH retrieved based on image edge detection was better than another two methods especially under heavy polluted episode. Then we applied this method to investigate the evolution of the mixing layer height during a pollution episode in December2016. MLH at Gucheng county showed the positive correlation with the concentration of particulate matters during the start of this pollution episode. The elevated pollution level in Gucheng was not associated with MLH's decrease, and the significantly increased particulate matters raised the boundary layer, which trapped the pollutants near the surface.

关键词： Mixing layer beijing–tianjin–hebei area Severe haze

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