江西赣州站大气CO变化特征及区域输送研究

Study on Atmospheric CO Variation Characteristics and Regional Transport at Ganzhou Station in Jiangxi

基于2018年12月—2019年11月江西省赣州站大气CO和CO_(2)浓度高精度在线观测资料,探究了赣州站CO浓度水平及其变化特征,厘清了该区域气团的轨迹,分析了区域大气输送的影响以及潜在排放源区分布特征,并对△CO_(2)和△CO浓度之间的相关性进行了分析。结果表明:(1)研究期内赣州站CO的平均浓度为415.0×10^(-9);赣州站CO浓度日变化特征具有季节差异性,在春夏季,夜间至清晨期间,CO浓度较高,午后CO浓度开始下降;在秋冬季,CO浓度日变化总体呈现白天高,夜间至清晨略低的特征。CO本底季节浓度呈现出明显的季节变化,1月出现峰值(694.8×10^(-9)),7月出现最小值(215.6×10^(-9))。(2)轨迹聚类分析表明,春、秋、冬季的赣州站高浓度CO主导气流来自江西省北部、湖北省东部、安徽省南部以及珠江三角洲地区;2019年1月28—29日污染事件的轨迹聚类分析表明,江西、安徽和江苏等省份的燃烧效率较高。(3)冬季的△CO和△CO_(2)呈强相关性,表明化石燃料和生物质燃烧以及人为排放活动对寒冷季节CO_(2)浓度变化的影响显著高于其他季节。

Based on the high-precision online observation data of atmospheric CO and CO_(2)concentrations at Ganzhou Station,Jiangxi Province from December 2018 to November 2019,the concentration levels and variation characteristics of CO at Ganzhou Station were studied,and the trajectory of air mass affecting the region was clarified.The influence of regional atmospheric transport and the distribution characteristics of potential emission sources were analyzed,and the correlation between△CO_(2)and△CO concentration was analyzed.The results showed that:(1)The average CO concentration in Ganzhou Station was 415.0×10^(-9).The diurnal variation characteristics of CO concentration showed seasonal differences.In spring and summer,the CO concentration was higher from night to morning,and began to decline in the afternoon.In autumn and winter,the diurnal variation of CO concentration was generally higher during the day and slightly lower from night to morning.The seasonal concentration of CO background showed a significant seasonal change.The maximum value occurs in January(694.8×10^(-9))and the minimum value occurs in July(215.6×10^(-9)).(2)The trajectory clustering analysis shows that the high concentration of CO in Ganzhou Station in spring,autumn and winter comes from the north of Jiangxi,the east of Hubei,the south of Anhui and the Pearl River Delta.The trajectory clustering analysis of pollution events from January 28 to 29,2019 shows that Jiangxi,Anhui and Jiangsu provinces have higher combustion efficiency.(3)The correlation analysis of△CO_(2)and△CO shows that△CO and△CO_(2)are strongly correlated in winter,indicating that anthropogenic emissions from fossil fuel and biomass combustion have a significantly higher impact on CO_(2)change in cold season than in other seasons.