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| 南京市大气PM2.5时空分布特征与潜在源区贡献分析 |
| Spatial-temporal Characteristics of Atmospheric PM2.5 and Contribution Analysis of Potential Source Areas for Nanjing |
| 投稿时间：2018-07-12 修订日期：2018-11-21 |
| DOI：10.14050/j.cnki.1672-9250.2019.47.040 |
| 中文关键词: PM2.5;时空特征;轨迹聚类;潜在源贡献因子;浓度权重轨迹分析 |
| 英文关键词: PM2.5;spatial-temporal;trajectory clustering;PSCF;CWT |
| 基金项目:国家自然科学基金项目（21767007）；贵州省科技厅（黔科合基础[2018]1111）；贵州师范大学博士科研启动基金项目；贵州师范大学"省级大学生创新创业训练计划"项目。 |
| 作者 | 单位 | E-mail | | 高月1, 孙荣国1,2, 陈卓1, 臧庆大1 | 1. 贵州师范大学 化学与材料科学学院, 贵阳 550025
2. 中国科学院地球化学研究所, 环境地球化学国家重点实验室, 贵阳 550081 | chenzhuo19@163.com |
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| 中文摘要: |
| 对2017年南京市区7个自动空气质量监测点的PM2.5质量浓度ρ（PM2.5）数据进行分析，采用克里金（Kringing）空间插值法、气流运动轨迹聚类、潜在源贡献因子法（PSCF）和浓度权重轨迹分析法（CWT）探讨了四季大气中ρ（PM2.5）的时空分布特征和潜在来源。结果显示，四季大气中ρ（PM2.5）均值由高到低依次为冬季（65.54 μg/m3）、春季（41.70 μg/m3）、秋季（35.18 μg/m3）和夏季（23.56 μg/m3），秦淮区四季大气中ρ（PM2.5）均最高。春季南京大气中ρ（PM2.5）易受黄海海岸和北方大陆性输送气流的影响，来自黄海方向的气流轨迹2贡献比例达51.65%，对应的ρ（PM2.5）为50.91 μg/m3；夏季南京大气中ρ（PM2.5）主要受江苏、东部海洋和南部沿海城市输送气流的影响，其中源自江苏的气流轨迹1对南京大气PM2.5贡献比例最大（33.64%），气流轨迹对应的ρ（PM2.5）为35 μg/m3；秋季南京大气中ρ（PM2.5）易受短距离的偏北气流影响，来自山西南部，河南中部、安徽中部的气流轨迹5对应的ρ（PM2.5）最高，出现概率（21.11%）和贡献比例（27.81%）均较高；冬季南京大气中ρ（PM2.5）主要受北方大陆性输送气流影响，来自俄罗斯、蒙古国东部、河北北部、北京、天津、山东中部的长距离气流轨迹4对应的ρ（PM2.5）最高，达109.8 μg/m3，其贡献比例为26.86%。PSCF和CWT分析发现，安徽、山东、浙江与江苏交界和黄海海岸是影响南京市空气质量的主要潜在源区，此外，湖北、北京、天津以及渤海海岸也是南京大气PM2.5的潜在源区。 |
| 英文摘要: |
| Data of PM2.5 from 7 automatic air quality monitoring stations of Nanjing in 2017 were discussed to examine the temporal and spatial characteristic of PM2.5 and it's sources. The analyzed methods include Kriging spatial interpolation method, Trajectory clustering of air flows, Potential Source Contribution Function (PSCF), and Concentration-Weighted Trajectory (CWT). The results indicated that the highest PM2.5 concentrations ρ(PM2.5) was observed in winter (65.54 μg/m3), followed by spring (41.70 μg/m3), autumn (35.18 μg/m3), and summer (23.56 μg/m3). All the highest ρ(PM2.5) were peaked in Qinhuai district in four seasons. In spring, the atmospheric PM2.5was easily affected by the coastal and northern continental transport airflow in Nanjing. The contribution of airflow trajectory 2 was up to 51.65% from the Yellow sea, and the ρ(PM2.5) was 50.91μg/m3. In summer, the atmospheric PM2.5 was mainly affected by the transport airflow in Jiangsu province, the Eastern seas and southern coastal cities, in which the contribution of airflow trajectory 1 originated from Jiangsu province was the largest contributor to atmospheric PM2.5 (33.64%) in Nanjing, and the corresponding airflow trajectory ρ(PM2.5) was 35 μg/m3. In autumn, the atmospheric PM2.5was susceptible to short-distance northerly airflow, and the airflow trajectory 5 corresponding to the south of Shanxi, central in Henan and central in Anhui, which was the highest ρ(PM2.5), with a higher occurrence probability (21.11%) and contribution proportion (27.81%). The atmospheric PM2.5 was mainly affected by the northern continental transport airflow in winter, which was the highest ρ(PM2.5) corresponding to the long-distance airflow trajectory 4 that from Russia, eastern in Mongolia, northern in Hebei, Beijing, Tianjin and central in Shandong province, up to 109.80 μg/m3, with the contribution rate of 26.86%. PSCF and CWT analysis showed that Anhui, Shandong, the Zhejiang province borders Jiangsu province and the Yellow sea coast were the main potential source regions, their affected the air quality in Nanjing, the Hubei province, Beijing, Tianjin and the coasts of the Yellow seas and the Bohai seas also made contributions to the air pollution in Nanjing. |
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