Variation characteristics and prediction of pollutant concentration during winter in Lanzhou New District, China

PM2.5 and PM10 were the main air pollutants during winter in Lanzhou New District,China.In this paper,WRF model output combined with hourly monitoring data of pollutant concentration was used to analyze characteristics of the concentration change and to study the relationship between meteorological elements and PM10/PM2.5 in Lanzhou New District in January,2018.Meanwhile,the concentration changes of PM2.5 and PM10 were predicted by wavelet analysis combined with BP neural network.The results show that:(1)Due to the cold front process in winter,PM2.5 was negatively correlated with the water vapor mixing rate.PM10 was positively correlated with air temperature and negatively correlated with air pressure.(2)There was an inversion layer in the atmosphere near the high value day of PM2.5 and PM10,the surface was controlled by low pressure,low wind speed,and the situation of low value day of PM2.5 was the opposite.On the day of high value of PM10,the air temperature below 600 hPa was higher,and the wind speed near the surface was also higher.(3)Wavelet analysis combined with BP(Back Propagation)neural network had a good prediction effect on PM2.5,which could basically reflect the hourly change of PM2.5 concentration.However,the simulation effect of PM10 was poor,and the input parameters of surrounding pollutants should be added to improve the prediction effect.

Near-surface wind environment in the Yarlung Zangbo River basin,southern Tibetan Plateau

Aeolian processes have been studied extensively at low elevations,but have been relatively little studied at high elevations.Aeolian sediments are widely distributed in the Yarlung Zangbo River basin,southern Tibetan Plateau,which is characterized by low pressure and low temperature.Here,we comprehensively analyzed the wind regime using data since 1980 from 11 meteorological stations in the study area,and examined the interaction between the near-surface wind and aeolian environment.The wind environment exhibited significant spatial and temporal variation,and mean wind speed has generally decreased on both annual and seasonal bases since 1980,at an average of 0.181 m/(s•10a).This decrease resulted from the reduced contribution of maximum wind speed,and depended strongly on variations of the frequency of sand-driving winds.The drift potential and related parameters also showed obvious spatial and temporal variation,with similar driving forces for the wind environment.The strength of the wind regime affected the formation and development of the aeolian geomorphological pattern,but with variation caused by local topography and sediment sources.The drift potential and resultant drift direction were two key parameters,as they quantify the dynamic conditions and depositional orientation of the aeolian sediments.Wind affected the spatial variation in sediment grain size,but the source material and complex topographic effects on the near-surface wind were the underlying causes for the grain size distribution of aeolian sands.These results will support efforts to control aeolian desertification in the basin and improve our understanding of aeolian processes in high-elevation environments.