Urban air quality and regional haze weather forecast for Yangtze River Delta region

被引:131
|
作者
Wang, Tijian [1 ]
Jiang, Fei [2 ]
Deng, Junjun [1 ,5 ]
Shen, Yi [1 ]
Fu, Qinyan [3 ]
Wang, Qian [3 ]
Fu, Yin [4 ]
Xu, Jianhua [4 ]
Zhang, Danning [4 ]
机构
[1] Nanjing Univ, Sch Atmospher Sci, Nanjing 210093, Jiangsu, Peoples R China
[2] Nanjing Univ, Int Inst Earth Syst Sci, Nanjing 210093, Jiangsu, Peoples R China
[3] Shanghai Environm Monitoring Ctr, Shanghai 200030, Peoples R China
[4] Nanjing Environm Monitoring Ctr, Nanjing 210008, Jiangsu, Peoples R China
[5] Chinese Acad Sci, Key Lab Urban Environm & Hlth, Inst Urban Environm, Xiamen 361021, Peoples R China
关键词
Air quality forecast; Haze weather forecast; Yangtze River Delta; Nanjing; Shanghai; CHEMICAL-CHARACTERIZATION; POLLUTION; EMISSIONS; TRENDS; MODEL; EXTINCTION; VISIBILITY; COMPONENTS; AEROSOLS; SYSTEM;
D O I
10.1016/j.atmosenv.2012.01.014
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Air pollution and haze weather have become more and more important environmental and meteorological issues in Yangtze River Delta (YRD) region of China. In order to foster urban and regional air quality management and realize operational prediction and early warning of air pollution and haze weather episode, an urban air quality forecasting system based on the new generation of weather research forecast and chemistry model WRF-Chem and a regional haze weather forecasting system based on Regional Atmospheric Environment Modeling System (RegAEMS) were applied in Shanghai. Nanjing and YRD area. More than one year runs and typical case studies show that WRF-Chem performed well in urban air quality forecast on surface concentrations of air pollutants such as SO2, NO2 and PM10. The accuracy rate of prediction on urban Air Pollution Index (API) is 50-83% and 80% for Shanghai and Nanjing, respectively. RegAEMS presents relatively good ability in forecast on regional haze weather. A new classification standard on haze level was proposed, which take the key parameters such as relative humidity, PM2.5 and visibility into account. It is estimated that RegAEMS predicts haze level with accuracy rate of 58 and 77% for Nanjing and Shanghai in YRD region. Many factors, including meteorology, emission inventory and chemical processes can be attributable to the forecast bias. However, from this study, it is highly suggested that improvements of emission inventory from construction dust, fugitive dust, soil dust, transportation and biomass burning are very crucial to get better performance on air quality and haze weather prediction. (C) 2012 Elsevier Ltd. All rights reserved.
引用
收藏
页码:70 / 83
页数:14
相关论文
共 50 条
  • [31] Spatiotemporal heterogeneity analysis of air quality in the Yangtze River Delta, China
    Miao, Lizhi
    Liu, Chengliang
    Yang, Xin
    Kwan, Mei-Po
    Zhang, Kai
    [J]. SUSTAINABLE CITIES AND SOCIETY, 2022, 78
  • [32] Empowering High-Quality Development in the Yangtze River Delta Region
    YE WEI
    SHEN JIAXUAN
    XU HAIYAN
    [J]. China Today, 2020, (10) : 62 - 64
  • [33] Regional low carbon development pathways for the Yangtze River Delta region in China
    Wu, Wei
    Zhang, Tingting
    Xie, Xiaomin
    Huang, Zhen
    [J]. ENERGY POLICY, 2021, 151
  • [34] Impacts of emissions along the lower Yangtze River on air quality and public health in the Yangtze River delta, China
    Sheng, Li
    Qin, Momei
    Li, Lin
    Wang, Chunlu
    Gong, Kangjia
    Liu, Ting
    Li, Jingyi
    Hu, Jianlin
    [J]. ATMOSPHERIC POLLUTION RESEARCH, 2022, 13 (06)
  • [35] Regional contribution to PM1 pollution during winter haze in Yangtze River Delta, China
    Tang, Lili
    Yu, Hongxia
    Ding, Aijun
    Zhang, Yunjiang
    Qin, Wei
    Wang, Zhuang
    Chen, Wentai
    Hua, Yan
    Yang, Xiaoxiao
    [J]. SCIENCE OF THE TOTAL ENVIRONMENT, 2016, 541 : 161 - 166
  • [36] Regional Development Quality of Yangtze River Delta: From the Perspective of Urban Population Agglomeration and Ecological Efficiency Coordination
    Xu, Zhenxiao
    Yin, Yongqiang
    [J]. SUSTAINABILITY, 2021, 13 (22)
  • [37] Regional spatial patterns and influencing factors of Haze Pollution in the Pearl River Delta region
    Yang, Yuanhua
    Tang, Shaojuan
    Tang, Dengli
    [J]. 2019 5TH INTERNATIONAL CONFERENCE ON ADVANCES IN ENERGY RESOURCES AND ENVIRONMENT ENGINEERING (ICAESEE 2019), 2020, 446
  • [38] Spatial differentiation of urban housing prices in integrated region of Yangtze River Delta
    Song, Weixuan
    Chen, Yanru
    Sun, Jie
    He, Miao
    [J]. Dili Xuebao/Acta Geographica Sinica, 2020, 75 (10): : 2109 - 2125
  • [39] Urban spatial correlation characteristics and intrinsic mechanism in the Yangtze River Delta region
    Cui, Yaoping
    Liu, Xuan
    Li, Dongyang
    Deng, Qingxin
    Xu, Jianing
    Shi, Xinyu
    Qin, Yaochen
    [J]. Dili Xuebao/Acta Geographica Sinica, 2020, 75 (06): : 1301 - 1315
  • [40] Digital Innovation and Urban Resilience: Lessons from the Yangtze River Delta Region
    Cao, Lihong
    Pan, Nengjie
    Lu, Yaoyi
    Su, Wenjie
    [J]. JOURNAL OF THE KNOWLEDGE ECONOMY, 2024,