违反了 PRIMARY KEY 约束 'PK_t_counter'。不能在对象 'dbo.t_counter' 中插入重复键。 语句已终止。 基于多元数据分析的我国PM2.5浓度及其主控因子的时空分布特征研究-Spatiotemporal Distribution Characteristics of PM2.5 Concentration and Its Main Control Factors in China Based on Multivariate Data Analysis
doi:  10.3878/j.issn.1006-9585.2018.18013
基于多元数据分析的我国PM2.5浓度及其主控因子的时空分布特征研究

Spatiotemporal Distribution Characteristics of PM2.5 Concentration and Its Main Control Factors in China Based on Multivariate Data Analysis
摘要点击 345  全文点击 306  投稿时间:2018-01-16  
查看HTML全文   下载PDF   查看/发表评论  下载PDF阅读器
基金:  国家自然科学基金41305113、41575123、41620104008、41611540340、91744206,国家科技支撑计划课题2014BAC22B04
中文关键词:  细颗粒物(PM2.5)  主模态  多元数据分析  排放场  气象场
英文关键词:  PM2.5  Main mode  Multivariate data analysis  Emission field  Meteorological field
                 
作者中文名作者英文名单位
姚雪峰YAO Xuefeng中国科学院大气物理研究所大气边界层物理与大气化学国家重点实验室, 北京 100029;中国科学院大学, 北京 100049;解放军 96631 部队, 北京 102206
葛宝珠GE Baozhu中国科学院大气物理研究所大气边界层物理与大气化学国家重点实验室, 北京 100029
郑海涛ZHENG Haitao中国科学院安徽光学精密机械研究所, 合肥 230031;中国科学技术大学, 合肥 230026
马宇飞MA Yufei解放军 96631 部队, 北京 102206
高超GAO Chao解放军 61741 部队, 北京 100094
王自发WANG Zifa中国科学院大气物理研究所大气边界层物理与大气化学国家重点实验室, 北京 100029
引用:姚雪峰,葛宝珠,郑海涛,马宇飞,高超,王自发.2018.基于多元数据分析的我国PM2.5浓度及其主控因子的时空分布特征研究[J].气候与环境研究,23(5):596-606,doi:10.3878/j.issn.1006-9585.2018.18013.
Citation:YAO Xuefeng,GE Baozhu,ZHENG Haitao,MA Yufei,GAO Chao,WANG Zifa.2018.Spatiotemporal Distribution Characteristics of PM2.5 Concentration and Its Main Control Factors in China Based on Multivariate Data Analysis[J].Climatic and Environmental Research(in Chinese),23(5):596-606,doi:10.3878/j.issn.1006-9585.2018.18013.
中文摘要:
      基于2013~2016年空气质量监测台站资料,利用经验正交分解、功率谱分析、BP典型相关分析等多元数据分析方法解析了中国地区细颗粒物(PM2.5)主要模态的时空特征,并与排放源和气象场建立了相关关系,得到以下结论:中国地区PM2.5场存在两个主要模态,其中第一主模态为一致增加模态,强度中心位于西北地区东部—华北南部地区;其时间序列呈显著下降趋势。第二主模态主要表现为南北反向变化的偶极子型分布,其大值区分别位于华北中南部和长江中下游地区。其中,PM2.5第一模态可以看作平均态,主要受平均排放场和环流场及大地形的影响,在北方的表现更为显著。PM2.5第二模态可看作偏离平均场的一种变化态,在冬季更可能和冷空气活动有关。冷空气的强弱决定了污染累积的位置以及输送的方式,其作用是使得南方的污染明显偏离平均态,故第二主模态在南方的表现更为显著。本研究有效地利用了多元数据分析方法研究了我国大气污染的演变机理,可为进一步认清大气污染的形成规律提供科技支撑。
Abstract:
      Based on 2013-2016 air quality monitoring station data, spatial and temporal characteristics of main modes of PM2.5 in China are analyzed using multivariate data analysis methods including empirical orthogonal decomposition, power spectral analysis and BP canonical correlation analysis. Their correlations with emission and meteorological fields are established. Major conclusions are as follows. There exist two main modes in the PM2.5 field in China. The first is an uniformly increasing mode with the large center located in eastern part of Northwest China and southern part of North China; its time series shows a significant downward trend. The second mode exhibits a dipole distribution with opposite changes in the north and south; the two large centers are located in the central and southern portions of North China and the middle and lower reaches of the Yangtze River, respectively. The first mode of PM2.5 can be regarded as the average state, which is mainly affected by the average emission field, the circulation field and large topography. Impacts of these factors are more significant in the north. The second mode can be regarded as a deviation from the average field, which is more likely associated with cold air activities in the winter. The strength of the cold air determines the location of accumulation of pollutants and the way of transport. Impacts of cold air activities often result in large deviations of pollutants from their averages in the south, and thereby the second mode is more significant in the south. This research effectively utilizes various multivariate data analysis methods to study the evolution mechanism of air pollution in China, which provides scientific and technological supports for further understanding the formation mechanisms for air pollution.
主办单位:中国科学院大气物理研究所 单位地址:北京市9804信箱
联系电话: 010-82995048,010-82995049传真:010-82995048 邮编:100029 Email:qhhj@mail.iap.ac.cn
本系统由北京勤云科技发展有限公司设计
京ICP备09060247号