globalchange  > 气候变化事实与影响
DOI: 10.1016/j.atmosenv.2016.10.046
Scopus记录号: 2-s2.0-84995617473
论文题名:
Air quality early-warning system for cities in China
作者: Xu Y; , Yang W; , Wang J
刊名: Atmospheric Environment
ISSN: 0168-2563
EISSN: 1573-515X
出版年: 2017
卷: 148
起始页码: 239
结束页码: 257
语种: 英语
英文关键词: Air quality early-warning systems ; Bio-inspire optimization algorithm ; Data preprocessing ; Fuzzy evaluation ; Hybrid forecasting model
Scopus关键词: Air pollution ; Air quality ; Alarm systems ; Data handling ; Developing countries ; Forecasting ; Optimization ; Pollution ; Pollution control ; Quality control ; Data preprocessing ; Early Warning System ; Fuzzy evaluation ; Hybrid forecasting ; Optimization algorithms ; Air pollution control ; air quality ; algorithm ; atmospheric modeling ; atmospheric pollution ; concentration (composition) ; data processing ; early warning system ; emission control ; experimental study ; fuzzy mathematics ; optimization ; pollution monitoring ; regulatory approach ; research work ; air pollutant ; air quality ; algorithm ; ambient air ; Article ; China ; city ; controlled study ; data processing ; forecasting ; fuzzy system ; human ; humpback whale ; nonhuman ; particulate matter ; priority journal ; process optimization ; support vector machine ; China
Scopus学科分类: Environmental Science: Water Science and Technology ; Earth and Planetary Sciences: Earth-Surface Processes ; Environmental Science: Environmental Chemistry
英文摘要: Air pollution has become a serious issue in many developing countries, especially in China, and could generate adverse effects on human beings. Air quality early-warning systems play an increasingly significant role in regulatory plans that reduce and control emissions of air pollutants and inform the public in advance when harmful air pollution is foreseen. However, building a robust early-warning system that will improve the ability of early-warning is not only a challenge but also a critical issue for the entire society. Relevant research is still poor in China and cannot always satisfy the growing requirements of regulatory planning, despite the issue's significance. Therefore, in this paper, a hybrid air quality early-warning system was successfully developed, composed of forecasting and evaluation. First, a hybrid forecasting model was proposed as an important part of this system based on the theory of “decomposition and ensemble” and combined with the advanced data processing technique, support vector machine, the latest bio-inspired optimization algorithm and the leave-one-out strategy for deciding weights. Afterwards, to intensify the research, fuzzy evaluation was performed, which also plays an indispensable role in the early-warning system. The forecasting model and fuzzy evaluation approaches are complementary. Case studies using daily air pollution concentrations of six air pollutants from three cities in China (i.e., Taiyuan, Harbin and Chongqing) are used as examples to evaluate the efficiency and effectiveness of the developed air quality early-warning system. Experimental results demonstrate that both the accuracy and the effectiveness of the developed system are greatly superior for air quality early warning. Furthermore, the application of forecasting and evaluation enables the informative and effective quantification of future air quality, offering a significant advantage, and can be employed to develop rapid air quality early-warning systems. © 2016 Elsevier Ltd
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/82413
Appears in Collections:气候变化事实与影响

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作者单位: School of Basic Medical Science, Lanzhou University, Lanzhou, China; School of Statistics, Dongbei University of Finance and Economics, Dalian, China

Recommended Citation:
Xu Y,, Yang W,, Wang J. Air quality early-warning system for cities in China[J]. Atmospheric Environment,2017-01-01,148
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