气候变化领域集成服务门户(CCPortal): The forecasting research of early warning systems for atmospheric pollutants: A case in Yangtze River Delta region

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DOI	10.1016/j.atmosenv.2015.06.032
	The forecasting research of early warning systems for atmospheric pollutants: A case in Yangtze River Delta region
	Song, Yiliao; Qin, Shanshan; Qu, Jiansheng; Liu, Feng
发表日期	2015
ISSN	1352-2310
EISSN	1873-2844
起始页码	58
结束页码	69
卷号	118
英文摘要	The issue of air quality regarding PM pollution levels in China is a focus of public attention. To address that issue, to date, a series of studies is in progress, including PM monitoring programs, PM source apportionment, and the enactment of new ambient air quality index standards. However, related research concerning computer modeling for PM future trends estimation is rare, despite its significance to forecasting and early warning systems. Thereby, a study regarding deterministic and interval forecasts of PM is performed. In this study, data on hourly and 12 h-averaged air pollutants are applied to forecast PM concentrations within the Yangtze River Delta (YRD) region of China. The characteristics of PM emissions have been primarily examined and analyzed using different distribution functions. To improve the distribution fitting that is crucial for estimating PM levels, an artificial intelligence algorithm is incorporated to select the optimal parameters. Following that step, an ANF model is used to conduct deterministic forecasts of PM. With the identified distributions and deterministic forecasts, different levels of PM intervals are estimated. The results indicate that the lognormal or gamma distributions are highly representative of the recorded PM data with a goodness-of-fit R-2 of approximately 0.998. Furthermore, the results of the evaluation metrics (MSE, MAPE and CP, AW) also show high accuracy within the deterministic and interval forecasts of PM, indicating that this method enables the informative and effective quantification of future PM trends. (C) 2015 Published by Elsevier Ltd.
关键词	PM2.5 CONCENTRATIONS MODEL CHINA PREDICTION QUALITY SITE
英文关键词	Particle matter (PM); Emissions distribution; Adaptive neuro-fuzzy (ANF) model; Dynamic interval forecasts; Forecasting and early warning systems
语种	英语
WOS研究方向	Environmental Sciences ; Meteorology & Atmospheric Sciences
来源期刊	ATMOSPHERIC ENVIRONMENT
来源机构	中国科学院西北生态环境资源研究院
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/134229
作者单位	Lanzhou Univ, Coll Earth & Environm Sci, MOE Key Lab Western Chinas Environm Syst, Lanzhou 730000, Peoples R China.
推荐引用方式 GB/T 7714	Song, Yiliao,Qin, Shanshan,Qu, Jiansheng,et al. The forecasting research of early warning systems for atmospheric pollutants: A case in Yangtze River Delta region[J]. 中国科学院西北生态环境资源研究院,2015,118.
APA	Song, Yiliao,Qin, Shanshan,Qu, Jiansheng,&Liu, Feng.(2015).The forecasting research of early warning systems for atmospheric pollutants: A case in Yangtze River Delta region.ATMOSPHERIC ENVIRONMENT,118.
MLA	Song, Yiliao,et al."The forecasting research of early warning systems for atmospheric pollutants: A case in Yangtze River Delta region".ATMOSPHERIC ENVIRONMENT 118(2015).