• 关键词：PM_2.5  后向轨迹  聚类分析  潜在源贡献因子法  浓度权重轨迹  长三角区域

• 基金项目：环境保护公益性行业科研专项（No.201409008）；上海市科委科技攻关项目（No.14DZ1202905）

• 朱书慧
• 1 国家环境保护城市大气复合污染成因与防治重点实验室, 上海 200233;2 上海市环境科学研究院, 上海 200233

• 周敏
• 1 国家环境保护城市大气复合污染成因与防治重点实验室, 上海 200233;2 上海市环境科学研究院, 上海 200233

• 乔利平
• 1 国家环境保护城市大气复合污染成因与防治重点实验室, 上海 200233;2 上海市环境科学研究院, 上海 200233

• 李莉
• 1 国家环境保护城市大气复合污染成因与防治重点实验室, 上海 200233;2 上海市环境科学研究院, 上海 200233

• 楼晟荣
• 1 国家环境保护城市大气复合污染成因与防治重点实验室, 上海 200233;2 上海市环境科学研究院, 上海 200233

• 严茹莎
• 1 国家环境保护城市大气复合污染成因与防治重点实验室, 上海 200233;2 上海市环境科学研究院, 上海 200233

• 王红丽
• 1 国家环境保护城市大气复合污染成因与防治重点实验室, 上海 200233;2 上海市环境科学研究院, 上海 200233

• 陶士康
• 1 国家环境保护城市大气复合污染成因与防治重点实验室, 上海 200233;2 上海市环境科学研究院, 上海 200233

• 陈长虹
• 1 国家环境保护城市大气复合污染成因与防治重点实验室, 上海 200233;2 上海市环境科学研究院, 上海 200233

• 摘要：2015年12月中国长三角区域经历了4次高浓度、大范围、长时间的颗粒物污染.本研究基于HYSPLIT后向轨迹模式结合GDAS（Global Data Assimilation System，全球资料同化系统）气象数据和长三角区域15个主要城市的PM_2.5质量浓度数据，利用轨迹聚类、潜在源贡献因子法（Potential Source Contribution Function，PSCF）和浓度权重轨迹法（Concentration-Weighted Trajectory，CWT）分析了2015年12月长三角区域主要气流轨迹方向和重污染过程中细颗粒物的潜在来源分布，探讨了不同污染过程的气象特征和影响气团分布.结果表明，2015年12月长三角区域主要受到来自西北和北方气流影响（B、C、D类），其出现概率分别为39.5%、20.0%和25.8%；西方内陆（A类）出现概率最低，仅为14.7%.西北内陆方向长距离输送（B类）对长三角区域空气质量影响较大，在此类气团主导下，长三角区域颗粒物（PM_2.5、PM₁₀）质量浓度和气态污染物（SO₂、NO₂、CO）质量浓度平均值分别为90.9、135.1、32.4、54.4和1200 μg·m^-3，且粗颗粒物比重较其它3类聚类高；经过东北海面气团（C类）携带的颗粒物浓度也较高，且PM_2.5/PM₁₀比值最高，可能是其水汽含量较高加剧了污染物的二次生成.PSCF和CWT分析结果表明，污染过程1（12月5-8日）期间，长三角区域PM_2.5浓度主要受内蒙东部、京津冀、山东和江苏东部等地影响；污染过程2（12月10-11日）和污染过程3（12月13-15日）期间，京津冀地区对长三角区域PM_2.5浓度的贡献都较低，污染过程2的主要潜在源区较为集中，主要为内蒙东部、辽宁、山东东部、江苏和上海；而污染过程3的潜在源区较广，内蒙西南地区、甘肃、山西、陕西、河南、河北南部、山东、安徽北部等地及长三角本地对区域PM_2.5浓度均有重要贡献；污染过程4（12月20-27日）持续时间最长，相较前3次污染过程，京津冀地区和西南地区对长三角区域PM_2.5浓度的贡献相对增加.总体来说，2015年12月4次污染过程期间长三角区域PM_2.5污染的潜在贡献源主要集中在华北和华东（长三角）地区，区域性污染和长距离输送对冬季长三角区域空气质量有重要影响.

• Abstract：Four heavy haze episodes occurred over the Yangtze River Delta (YRD) in December 2015. In this study, impacts of major air mass trajectories on PM_2.5 concentrations in 15 cities in the YRD area and their potential source regions were analyzed by using cluster analysis, potential source contribution function (PSCF) and concentration-weighted trajectory (CWT) methods based on HYSPLIT backward simulation combined with global data assimilation system (GDAS) meteorological data. Meteorological and air mass characteristics under different pollution episodes were also analyzed. Results showed that the dominant airflows in the YRD were from the north to northwest in December 2015, with the frequencies in cluster B, C and D of 39.5%, 20.0% and 25.8%, respectively. The frequency of Cluster A is the lowest (14.7%). Air mass from northwestern inland had a significant impact on air quality in the YRD. The average mass concentrations of PM_2.5, PM₁₀, SO₂, NO₂ and CO under influence of cluster B air mass reached (90.9±59.0), (135.1±70.5), (32.4±15.3), (54.4±21.1) and (1200±500) μg·m^-3, respectively. The ratio of PM_2.5/PM₁₀ is low compared with other clusters. PM_2.5 concentrations and PM_2.5/PM₁₀ ratio under influence of northeastern marine air mass (cluster C) are also very high, which was probably due to the high vapor content that was favorable for secondary formation. The PSCF and CWT results showed that the major source regions to PM_2.5 in the 15 cities during haze episode 1 (from December 5^th to 8^th) were Inner Mongolia, Jingjinji region, Shandong and Jiangsu. The impacts from Jingjinji region decreased significantly during both episode 2 and episode 3. During episode 2 (from December 10^th to 11^th), the major area affecting PM_2.5 in the YRD were eastern Inner Mongolia, Liaoning, eastern Shandong, Jiangsu and Shanghai, while the potential regions affecting PM_2.5 were much wider during episode 3 (from December 13^th to 15^th). Southwestern Inner Mongolia, Gansu, Shanxi, Shanxi, Henan, Southern Hebei, Shandong, northern Anhui and also YRD local area all had great contributions. Episode 4 (from December 20^th to 27^th) lasted for more than one week and were impacted from Jingjinji and southwestern area. In conclusion, besides the YRD itself, northern China and eastern China were major potential area which had influence on PM_2.5 concentrations in the YRD region. In addition, super-regional transport had important impacts on YRD air quality in winter.

• Key words：PM_2.5  backward trajectory  cluster analysis  potential source contribution function(PSCF)  concentration-weighted trajectory(CWT)  Yangtze River Delta (YRD)

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