摘要
通过采集北京城区2015年冬夏季代表月1月和7月大气细颗粒物PM2.5样品,结合相关气象数据,分析研究了北京城区冬夏季PM2.5及其中有机碳(OC)和元素碳(EC)的质量浓度变化和污染特征.利用ρ(OC)/ρ(EC)最小比值法估算了二次有机碳(SOC)质量浓度,并采用后向轨迹模型和聚类分析法,研究了气团传输对灰霾形成的影响.结果表明,PM2.5和含碳气溶胶质量浓度表现为冬季>夏季,霾日>非霾日.SOC是OC的重要组成部分,冬季占OC质量浓度的47.16%,夏季达55.54%.北京市冬季霾日的气团轨迹主要为西北高空气团和局地气团,其中来自京津冀周边的局地气团传输对灰霾污染有较大贡献;夏季霾日的气团轨迹主要为东南气团、西北气团和西南气团,其中来自南方的气团轨迹所占频率较高,对灰霾污染贡献较大.因此加强京津冀及周边地区大气污染治理联防联控,对北京市空气质量改善具有重要意义.
The atmospheric PM2. 5 samples in urban of Beijing were collected in January and July,2015,which represented the winter and summer respectively. The samples were analyzed for the mass concentration changes and pollution characteristics of PM2. 5,organic carbon（ OC） and elemental carbon（ EC）,combining with relevant meteorological data. Moreover,the mass concentrations of secondary organic carbon（ SOC） were estimated by ρ（ OC）/ρ（ EC） minimum ratio method,and the effect of air mass transport on haze formation was studied by using of backward trajectory and cluster analysis model.Results showed that the mass concentrations of PM2. 5 and carbonaceous aerosol were expressed as winter summer,haze weather non-haze weather. SOC is an important part of OC,accounting for47. 16% in winter,55. 54% in summer,respectively. The air mass trajectories in haze weather in winter were mainly controlled by northwest high air mass and local air mass,among which the local air mass transport from Beijing-Tianjin-Hebei（ BTH） region was a great contribution to the haze pollution. While,the air mass trajectories in haze weather in summer were mainly affected by southeast air mass,northwest air mass and southwest air mass. The frequency of air mass trajectories from the south was higher and have a greater contribution to haze pollution. Therefore,strengthening the air pollution joint prevention and control in Beijing-Tianjin-Hebei and its surrounding areas is of great significance for improving air quality in Beijing.
出处
《北京工业大学学报》
CAS
CSCD
北大核心
2018年第3期463-472,共10页
Journal of Beijing University of Technology
基金
国家自然科学基金资助项目(91544232
51638001)
国家科技支撑计划课题资助项目(2014BAC23B00)
北京市科技计划资助项目(Z141100001014002
D16110900440000)
