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2011~2020年华北平原气溶胶光学厚度时空分布特征及潜在源分析
引用本文:王 利,徐翠玲,徐 甫,高 琦.2011~2020年华北平原气溶胶光学厚度时空分布特征及潜在源分析[J].延边大学理工学报,2021,0(6):1018-1032.
作者姓名:王 利  徐翠玲  徐 甫  高 琦
作者单位:(长安大学 地质工程与测绘学院,陕西 西安 710054)
摘    要:随着经济高速增长和城市化进程不断加快,华北平原区域性空气污染问题愈演愈烈。针对该区域开展长时序气溶胶光学厚度时空分布特征和潜在源分析研究,对华北平原大气污染治理具有重要意义。基于长时序MODIS/Terra C6.1 MOD04_L2气溶胶光学厚度产品,分析华北平原气溶胶光学厚度的时空分布特征,并利用后向轨迹聚类分析讨论华北平原7个重点城市气团输送的季节变化,并以污染较为严重的河北石家庄为例进行潜在源分析和浓度权重分析,探究影响其大气质量的污染物潜在源区。结果表明:2011~2020年华北平原气溶胶光学厚度月均值呈显著的周期性变化,以年为周期,每个周期内峰值一般出现在6月至8月; 气溶胶光学厚度月际年内呈单峰分布,峰值出现在6月(0.75),最小值出现在12月(0.37); 气溶胶光学厚度季均值从大到小依次为夏季(0.67)、春季(0.59)、冬季(0.49)、秋季(0.46); 10年间气溶胶光学厚度呈下降趋势,整体下降幅度达36.84%,其中2011年最高(0.72),2018年最低(0.45); 华北平原7个重点城市春、夏、秋、冬四季主要受短距离气团输送影响较大,长距离气团输送影响较小; 2014~2020年河北石家庄的空气质量优良天数占比相对较小,空气质量状况差,影响其空气质量的污染物多为本地生成,同时也受周边省市近距离输送的影响。

关 键 词:气溶胶光学厚度  MODIS  空气质量指数  后向轨迹  聚类分析  潜在源贡献因子分析  浓度权重分析  华北平原

Temporal and Spatial Distribution Characteristics,and Potential Source Analysis of Aerosol Optical Depth in North China Plain from 2011 to 2020
WANG Li,XU Cui-ling,XU Fu,GAO Qi.Temporal and Spatial Distribution Characteristics,and Potential Source Analysis of Aerosol Optical Depth in North China Plain from 2011 to 2020[J].Journal of Yanbian University (Natural Science),2021,0(6):1018-1032.
Authors:WANG Li  XU Cui-ling  XU Fu  GAO Qi
Affiliation:(School of Geological Engineering and Geomatics, Chang'an University, Xi'an 710054, Shaanxi, China)
Abstract:With the rapid economic growth and the acceleration of urbanization, the regional air pollution problem in North China Plain has intensified. The study on temporal and spatial distribution characteristics, and potential sources of long-term aerosol optical depth in North China Plain is of great significance to the control of air pollution. Based on the long-time MODIS/Terra C6.1 MOD04_L2 aerosol optical depth product, the temporal and spatial distribution characteristics of aerosol optical depth in North China Plain were analyzed, and the backward trajectory cluster analysis was used to discuss the seasonal changes of air mass transportation in 7 major cities of North China Plain. As an example, Shijiazhuang in Hebei, which is more polluted, was used to explore the potential sources of pollutants by potential sources and concentration-weight analysis. ① The monthly average value of aerosol optical depth in North China Plain has a significant periodic change from 2011 to 2020; taking the year as the cycle, and the peak value in each cycle generally appears from June to August. Aerosol optical depth has a single-peak distribution during the year; the peak value appears in June(0.75), and the minimum value appears in December(0.37). The seasonal average values of aerosol optical depth in North China Plain are in order with summer(0.67), spring(0.59), winter(0.49)and autumn(0.46). Aerosol optical depth shows a downward trend from 2011 to 2020 with an overall decrease of 36.84%; the highest is in 2011(0.72), and the lowest is in 2018(0.45). ② The spring, summer, autumn and winter of 7 major cities in North China Plain are mainly affected by short-distance air mass transportation, and less affected by long-distance air mass transportation. ③ From 2014 to 2020, the good air quality days of Shijiazhuang in Hebei account for a relatively small proportion, and the air quality is poor; most of pollutants that affect air quality of Shijiazhuang in Hebei are generated locally, and are also affected by the close transportation of surrounding provinces and cities.
Keywords:aerosol optical depth  MODIS  air quality index  backward trajectory  cluster analysis  potential source contribution function analysis  concentration-weight analysis  North China Plain
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