Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, School of Environmental Science and Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China.
Jiangsu Environmental Monitoring Center, Nanjing 210036, China.
J Environ Sci (China). 2020 Jul;93:13-22. doi: 10.1016/j.jes.2020.02.027. Epub 2020 Mar 12.
Ground-level ozone (O) has become a critical pollutant impeding air quality improvement in Yangtze River Delta region of China. In this study, we present O pollution characteristics based on one-year online measurements during 2016 at an urban site in Nanjing, Jiangsu Province. Then, the sensitivity of O to its precursors during 2 O pollution episodes in August was analyzed using a box model based on observation (OBM). The relative incremental reactivity (RIR) of hydrocarbons was larger than other precursors, suggesting that hydrocarbons played the dominant role in O formation. The RIR values for NO ranged from -0.41%/% to 0.19%/%. The O sensitivity was also analyzed based on relationship of simulated O production rates with reductions of VOC and NO derived from scenario analyses. Simulation results illustrate that O formation was between VOCs-limited and transition regime. Xylenes and light alkenes were found to be key species in O formation according to RIR values, and their sources were determined using the Positive Matrix Factorization (PMF) model. Paints and solvent use was the largest contributor to xylenes (54%), while petrochemical industry was the most important source to propene (82%). Discussions on VOCs and NO reduction schemes suggest that the 5% O control goal can be achieved by reducing VOCs by 20%. To obtain 10% O control goal, VOCs need to be reduced by 30% with VOCs/NO larger than 3:1.
地面臭氧（O）已成为阻碍中国长江三角洲地区空气质量改善的关键污染物。本研究基于 2016 年江苏省南京市一个城市站点的一年在线监测数据，介绍了 O 污染特征。然后，利用基于观测的箱模型（OBM）分析了 2 次 8 月 O 污染事件期间 O 对其前体物的敏感性。与其他前体物相比，烃类的相对增量反应性（RIR）较大，表明烃类在 O 形成中起主导作用。NO 的 RIR 值范围为-0.41%/%至 0.19%/%。还根据情景分析得出的 VOC 和 NO 减少量与模拟 O 生成速率的关系分析了 O 的敏感性。模拟结果表明，O 的形成处于 VOCs 限制和过渡状态之间。根据 RIR 值，发现二甲苯和轻烯烃是 O 形成的关键物种，并用正定矩阵因子分解（PMF）模型确定了它们的来源。油漆和溶剂使用是二甲苯（54%）的最大来源，而石化工业是丙烯（82%）的最重要来源。对 VOCs 和 NO 减排方案的讨论表明，通过减少 20%的 VOCs 可以实现 5%的 O 控制目标，而要达到 10%的 O 控制目标，需要将 VOCs 减少 30%，同时要求 VOCs/NO 大于 3:1。
