薄雾
化学
污染
硝酸盐
δ18O
环境化学
分析化学(期刊)
稳定同位素比值
物理
有机化学
生态学
量子力学
生物
作者
Xinxin Feng,Yingjun Chen,Shaofeng Chen,Ping Yu,Zeyu Liu,Min Jiang,Yinchang Feng,Lina Wang,Li Li,Jianmin Chen
标识
DOI:10.1021/acs.est.3c07590
摘要
δ18O is widely used to track nitrate (NO3-) formation but overlooks NO3 radical reactions with hydrocarbons (HCs), particularly in heavily emitting hazes. This study introduces high-time resolution Δ17O-NO3- as a powerful tool to quantify NO3- formation during five hazes in three cities. Results show significant differences between Δ17O-NO3- and δ18O-NO3- in identifying NO3- formation. δ18O-NO3- results suggested N2O5 hydrolysis (62.0-88.4%) as the major pathway of NO3- formation, while Δ17O-NO3- shows the NO3- formation contributions of NO2 + OH (17.7-66.3%), NO3 + HC (10.8-49.6%), and N2O5 hydrolysis (22.9-33.3%), revealing significant NO3 + HC contribution (41.7-56%) under severe pollution. Furthermore, NO3- formation varies with temperatures, NOx oxidation rate (NOR), and pollution levels. Higher NO2 + OH contribution and lower NO3 + HC contribution were observed at higher temperatures, except for low NOR haze where higher NO2 + OH contributions were observed at low temperatures (T ← 10 °C). This emphasizes the significance of NO2 + OH in emission-dominated haze. Contributions of NO2 + OH and NO3 + HC relate to NOR as positive (fP1 = 3.0*NOR2 - 2.4*NOR + 0.8) and negative (fP2 = -2.3*NOR2 + 1.8*NOR) quadratic functions, respectively, with min/max values at NOR = 0.4. At mild pollution, NO2 + OH (58.1 ± 22.2%) dominated NO3- formation, shifting to NO3 + HC (35.5 ± 16.3%) during severe pollution. Additionally, high-time resolution Δ17O-NO3- reveals that morning-evening rush hours and high temperatures at noon promote the contributions of NO3 + HC and NO2 + OH, respectively. Our results suggested that the differences in the NO3- pathway are attributed to temperatures, NOR, and pollution levels. Furthermore, high-time resolution Δ17O-NO3- is vital for quantifying NO3 + HC contribution during severe hazes.
科研通智能强力驱动
Strongly Powered by AbleSci AI