摘要
当前,细颗粒物(PM_(2.5))和臭氧(O_(3))已成为我国的两大主要空气污染物,特别是在人口密集的区域。PM_(2.5)和O_(3)污染程度强烈依赖于天气过程和人为排放,二者不仅影响社会经济健康发展,而且影响人体健康。为了探索PM_(2.5)和O_(3)的协同控制方法,分析两者相关性,掌握其主要影响因素,选取南充市主城区(顺庆区、高坪区、嘉陵区)为研究对象,以四川省空气质量监测网络管理系统中自动监测数据为基础,利用Origin、Excel、SPSS等软件,分析了该市环境空气中PM_(2.5)和O_(3)的污染现状、时空变化趋势以及影响因素,并探讨了二者的相关性。结果表明:①2018~2022年南充市主城区环境空气中PM_(2.5)、O_(3)年际变化整体呈下降趋势,近5年O_(3)浓度均达标,但2022年O_(3)出现反弹。②PM_(2.5)、O_(3)均表现出明显季节变化趋势,其中PM_(2.5)呈现冬春高、夏秋低的“河谷型”变化趋势,而O_(3)截然相反。③O_(3)峰值主要出现在15:00-17:00,PM_(2.5)多在23:00开始上升。④O_(3)和PM_(2.5)空间变化趋势与各自地理位置具有一定联系。
Rapid economic development over the past decades has caused serious air pollution problems in China,with high concentrations of fine particulate matter(PM_(2.5))and ozone(O_(3)),while PM_(2.5) and O_(3) have become the two major air pollutants in China in recent years,especially in densely populated cities.Fluctuations in PM_(2.5) and O_(3) are strongly dependent on weather processes and anthropogenic emissions.The co-pollution of PM_(2.5) and O_(3) not only harms human health,but also harms social economy,which has become a key issue in air pollution control and co-management.In order to integrate the control methods of PM_(2.5) and O_(3),it is necessary to analyze the correlation between PM_(2.5) and O_(3) concentration and understand the impact of meteorology on the two pollutants.To explore the mechanism of PM_(2.5) and O_(3) pollution,the main urban area of Nanchong City(Shunqing District,Gaoping District and Jialing District)is selected as the research area.Based on the data of Sichuan Province air quality monitoring network management system,origin and Excel are used to analyze the pollution status,spatio-temporal trends and influencing factors of PM_(2.5) and O_(3) in the ambient air of Nanchong City.The correlation between them is discussed by Pearson.The results showed that:①the interannual variation of PM_(2.5) and O_(3) pollution in the main urban area of Nanchong City showed a downward trend from 2018 to 2022.O_(3) pollution rebounded in 2022,and the O_(3) concentration reached the standard in the past five years.②from the perspective of seasonal variation,PM_(2.5) showed a"valley pattern"of high in winter and spring and low in summer and autumn.O_(3) presents a completely opposite trend to PM_(2.5),that is,the"peak type"change trend is high in summer and autumn and low in winter and spring.By comparing the observation results of PM_(2.5) and O_(3),it is found that both PM_(2.5) and O_(3) show obvious seasonal changes.③O_(3) exceeding the standard usually occurs at 3 to 5 PM,while PM_(2.5) conc
作者
刘骏
夏杰
杜鑫
Liu Jun;Xia Jie;Du Xin(Nanchong Ecological and Environment Monitoring Center Station of Sichuan Province,Nanchong 637600,Sichuan,China)
出处
《绿色科技》
2024年第18期155-162,共8页
Journal of Green Science and Technology
基金
四川省生态环境保护科技计划项目(编号:2024HB19)。
