Pei Cheng-Lei, Mu Jiang-Shan, Zhang Ying-Nan, Shen Heng-Qing, Chen Yu-Ru, Huang Jie-Sheng, Ding Hao-Ran, Li Cheng-Liu
Guangzhou Ecological and Environmental Monitoring Center of Guangdong Province, Guangzhou 510060, China.
Guangdong Provincial Observation and Research Station for Climate Environment and Air Quality Change in the Pearl River Estuary, Guangzhou 510275, China.
Huan Jing Ke Xue. 2021 Apr 8;42(4):1615-1625. doi: 10.13227/j.hjkx.202009058.
A six-day ozone pollution episode in Guangzhou in early October 2018 was analyzed with the application of a Lagrangian photochemical trajectory model to trace the sources of ozone, quantify the contributions of different regions, and evaluate the effects of emission reduction measures targeted at different emission sectors and different precursors on ozone pollution. The results showed that during the ozone pollution episode, the maximum daily 8 h ozone exceeded 160 μg·m and the highest value reached 271 μg·m. The average concentrations of nitrogen oxides and volatile organic compounds (VOCs) were (77.7±42.8) μg·m and (71.9±56.2) μg·m, respectively. Aromatics and alkenes were the dominant reactive VOCs, with contributions of 38% and 30% to·OH reactivity and 51% and 16% to ozone formation potential, respectively. The ozone pollution in Guangzhou during this episode was affected by three types of air masses, with the primary source regions of Guangzhou, Guangdong Province, and regions outside Guangdong Province. For all three air mass types, ozone production in these source region was controlled by VOCs. Sensitivity tests showed that, in the primary source regions, reducing the emissions of VOCs is more effective than reducing NO in terms of reducing ozone concentrations. Under the condition of full emission reduction, regulating traffic emissions could substantially reduce ozone levels by 14.6%-21.0% in Guangzhou, which was a more significant reduction than regulating controlled industry (8.4%-15.3%), power plant (0.9%-6.2%) and residential (2.3%-4.7%) emissions. However, the traffic emission reduction is not as effective (induced ozone reduction<10%) when the emissions reduction ratio is lower than 90%. In addition, biogenic emissions in the Pearl River Delta also substantially contributed to the ozone levels under certain circumstances, as indicated by the ozone reduction up to 19% when biogenic emissions were shut off.
利用拉格朗日光化学轨迹模型对2018年10月初广州为期六天的臭氧污染事件进行了分析,以追踪臭氧来源、量化不同区域的贡献,并评估针对不同排放部门和不同前体的减排措施对臭氧污染的影响。结果表明,在臭氧污染事件期间,日最大8小时臭氧浓度超过160μg·m,最高值达到271μg·m。氮氧化物和挥发性有机化合物(VOCs)的平均浓度分别为(77.7±42.8)μg·m和(71.9±56.2)μg·m。芳烃和烯烃是主要的活性VOCs,对·OH反应活性的贡献分别为38%和30%,对臭氧生成潜势的贡献分别为51%和16%。此次事件期间广州的臭氧污染受三类气团影响,主要源区为广州、广东省以及广东省以外的区域。对于所有这三类气团,这些源区的臭氧生成均受VOCs控制。敏感性测试表明,在主要源区,减少VOCs排放比减少NO排放对降低臭氧浓度更有效。在全面减排的情况下,调控交通排放可使广州的臭氧水平大幅降低14.6%-21.0%,这一比调控重点行业(8.4%-15.3%)、电厂(0.9%-6.2%)和居民排放(2.3%-4.7%)的减排效果更为显著。然而,当减排比例低于90%时,交通减排效果不佳(臭氧减少量<10%)。此外,珠江三角洲的生物源排放在某些情况下也对臭氧水平有显著贡献,关闭生物源排放时臭氧减少量高达19%即表明了这一点。