Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science & Technology, Nanjing, China.
Nanjing Gaochun district Meteorological Bureau, Nanjing, China.
PLoS One. 2018 Dec 7;13(12):e0208944. doi: 10.1371/journal.pone.0208944. eCollection 2018.
China has been troubled by high concentrations of fine particulate matter (PM2.5) for many years. Up to now, the pollutant sources are not yet fully understood and the control approach still remains highly uncertain. In this study, four month-long (January, April, July and October in 2015) WRF-Chem simulations with different sensitivity experiments were conducted in the Yangtze River Delta (YRD) region of eastern China. The simulated results were compared with abundant meteorological and air quality observations at 138 stations in 26 YRD cities. Our model well captured magnitudes and variations of the observed PM2.5, with the normal mean biases (NMB) less than ±20% for 19 out of the 26 YRD cities. A series of sensitivity simulations were conducted to quantify the contributions from individual source sectors and from different regions to the PM2.5 in the YRD region. The calculated results show that YRD local source contributed 64% of the regional PM2.5 concentration, while outside transport contributed the rest 36%. Among the local sources, industry activity was the most significant sector in spring (25%), summer (36%) and fall (33%), while residential source was more important in winter (38%). We further conducted scenario simulations to explore the potential impacts of varying degrees of emission controls on PM2.5 reduction. The result demonstrated that regional cooperative control could effectively reduce the PM2.5 level. The proportionate emission controls of 10%, 20%, 30%, 40% and 50% could reduce the regional mean PM2.5 concentrations by 10%, 19%, 28%, 37% and 46%, respectively, and for places with higher ambient concentrations, the mitigation efficiency was more significant. Our study on source apportionment and emission controls can provide useful information on further mitigation actions.
中国多年来一直受到细颗粒物（PM2.5）高浓度的困扰。到目前为止，污染源尚未完全了解，控制方法仍然高度不确定。在本研究中，在中国东部的长江三角洲（YRD）地区进行了四次为期四个月（2015 年 1 月、4 月、7 月和 10 月）的 WRF-Chem 模拟，并进行了不同敏感性实验。将模拟结果与 26 个 YRD 城市的 138 个站点的大量气象和空气质量观测进行了比较。我们的模型很好地捕捉到了观测到的 PM2.5 的大小和变化，其中 26 个 YRD 城市中有 19 个的正常平均偏差（NMB）小于±20%。进行了一系列敏感性模拟，以量化各个源部门和不同地区对 YRD 地区 PM2.5 的贡献。计算结果表明，YRD 本地源贡献了区域 PM2.5 浓度的 64%，而外部运输贡献了其余的 36%。在本地源中，工业活动在春季（25%）、夏季（36%）和秋季（33%）最为显著，而在冬季（38%），居民源更为重要。我们进一步进行了情景模拟，以探索不同程度的排放控制对 PM2.5 减排的潜在影响。结果表明，区域合作控制可以有效地降低 PM2.5 水平。排放控制比例为 10%、20%、30%、40%和 50%，可分别降低区域平均 PM2.5 浓度 10%、19%、28%、37%和 46%，而环境浓度较高的地区，缓解效率更为显著。我们对源分配和排放控制的研究可以为进一步的缓解行动提供有用的信息。
