Objective To investigate the seasonal characteristics and the sources of elements and ions with different sizes in the aerosols in Beijing. Methods Samples of particulate matters （PM2,5）, PM10, and total suspended p...Objective To investigate the seasonal characteristics and the sources of elements and ions with different sizes in the aerosols in Beijing. Methods Samples of particulate matters （PM2,5）, PM10, and total suspended particle （TSP） aerosols were collected simultaneously in Beijing from July 2001 to April 2003. The aerosol was chemically characterized by measuring 23 elements and 18 water-soluble ions by inductively coupled plasma-atomic emission spectroscopy （ICP-AES） and ion chromatography （IC）, respectively. Results The samples were divided into four categories： spring non-dust, spring dust, summer dust, and winter dust. TSP, PM10, and PM2.5 were most abundant in the spring dust, and the least in summer dust. The average mass ratios of PM〉10, PM2,5-10, and PM2.5 to TSP confirmed that in the spring dust both the large coarse （PM〉10） and fine particles （PM2.5） contributed significantly in summer PM2.5, PM2,5-10, and PM〉10 contributed similar fractions to TSP, and in winter much PM2.5. The seasonal variation characteristics of the elements and ions were used to divide them into four groups： crustal, pollutant, mixed, and secondary. The highest levels of crustal elements, such as AI, Fe, and Ca, were found in the dust season, the highest levels of pollutant elements and ions, such as As, F, and Cl^-, were observed in winter, and the highest levels of secondary ions （SO4^2-, NO3^-, and NH4^＋） were seen both in summer and in winter. The mixed group （Eu, Ni, and Cu） showed the characteristics of both crustal and pollutant elements. The mineral aerosol from outside Beijiug contributed more than that from the local part in all the reasons but summer, estimated using a newly developed element tracer technique.展开更多
Based on the monitoring data of visibility,particulate matter（ PM2. 5 and PM10） and atmospheric pollutants（ SO2,NO2,CO,and O3）,and meteorological factors（ temperature,humidity,and wind speed） at the six automati...Based on the monitoring data of visibility,particulate matter（ PM2. 5 and PM10） and atmospheric pollutants（ SO2,NO2,CO,and O3）,and meteorological factors（ temperature,humidity,and wind speed） at the six automatic air monitoring stations in Binzhou City from December 2016 to February 2017,the correlations between visibility and influencing factors were analyzed to study the main influencing factors of atmospheric visibility. The results showed that the daily average concentration of particulate matter negatively correlated with atmospheric visibility,and the correlation between PM2. 5 concentration and atmospheric visibility was more obvious than that of PM10 concentration. Among atmospheric pollutants,the daily average concentration of CO,NO2 and SO2 also negatively correlated with atmospheric visibility,while there was a positive correlation between visibility and the daily average concentration of O3. Daily average temperature and wind speed positively correlated with visibility,while relative humidity negatively correlated with visibility. Wind speed,relative humidity and PM2. 5 had strong correlation with visibility,and the linear correlation coefficient R2 was 0. 501 6,0. 446 6,and 0. 205 8 respectively,so wind speed,relative humidity,and PM2. 5 were the main factors influencing the decrease of atmospheric visibility on a hazy day in winter.展开更多
基金This work was supported by the National Natural Science Foundation of China (Grant No. 29837190, 30230310, 20077004, and 20477004),and Beijing Natural Science Foundation (Grant No. 8991002 and 8041003).
文摘Objective To investigate the seasonal characteristics and the sources of elements and ions with different sizes in the aerosols in Beijing. Methods Samples of particulate matters （PM2,5）, PM10, and total suspended particle （TSP） aerosols were collected simultaneously in Beijing from July 2001 to April 2003. The aerosol was chemically characterized by measuring 23 elements and 18 water-soluble ions by inductively coupled plasma-atomic emission spectroscopy （ICP-AES） and ion chromatography （IC）, respectively. Results The samples were divided into four categories： spring non-dust, spring dust, summer dust, and winter dust. TSP, PM10, and PM2.5 were most abundant in the spring dust, and the least in summer dust. The average mass ratios of PM〉10, PM2,5-10, and PM2.5 to TSP confirmed that in the spring dust both the large coarse （PM〉10） and fine particles （PM2.5） contributed significantly in summer PM2.5, PM2,5-10, and PM〉10 contributed similar fractions to TSP, and in winter much PM2.5. The seasonal variation characteristics of the elements and ions were used to divide them into four groups： crustal, pollutant, mixed, and secondary. The highest levels of crustal elements, such as AI, Fe, and Ca, were found in the dust season, the highest levels of pollutant elements and ions, such as As, F, and Cl^-, were observed in winter, and the highest levels of secondary ions （SO4^2-, NO3^-, and NH4^＋） were seen both in summer and in winter. The mixed group （Eu, Ni, and Cu） showed the characteristics of both crustal and pollutant elements. The mineral aerosol from outside Beijiug contributed more than that from the local part in all the reasons but summer, estimated using a newly developed element tracer technique.
文摘Based on the monitoring data of visibility,particulate matter（ PM2. 5 and PM10） and atmospheric pollutants（ SO2,NO2,CO,and O3）,and meteorological factors（ temperature,humidity,and wind speed） at the six automatic air monitoring stations in Binzhou City from December 2016 to February 2017,the correlations between visibility and influencing factors were analyzed to study the main influencing factors of atmospheric visibility. The results showed that the daily average concentration of particulate matter negatively correlated with atmospheric visibility,and the correlation between PM2. 5 concentration and atmospheric visibility was more obvious than that of PM10 concentration. Among atmospheric pollutants,the daily average concentration of CO,NO2 and SO2 also negatively correlated with atmospheric visibility,while there was a positive correlation between visibility and the daily average concentration of O3. Daily average temperature and wind speed positively correlated with visibility,while relative humidity negatively correlated with visibility. Wind speed,relative humidity and PM2. 5 had strong correlation with visibility,and the linear correlation coefficient R2 was 0. 501 6,0. 446 6,and 0. 205 8 respectively,so wind speed,relative humidity,and PM2. 5 were the main factors influencing the decrease of atmospheric visibility on a hazy day in winter.
