Simulation of surface ozone over Hebei province, China using Kolmogorov-Zurbenko and artificial neural network (KZ-ANN) combined model
Simulation of surface ozone over Hebei province, China using Kolmogorov-Zurbenko and artificial neural network (KZ-ANN) combined model
复制标题
利用 Kolmogorov-Zurbenko 和人工神经网络 (KZ-ANN) 组合模型模拟中国河北省地表臭氧
DOI：
10.1016/j.atmosenv.2021.118599
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发表时间：
2021-09
影响因子：
5
通讯作者：
Hong Zhao
中科院分区：
文献类型：
--
作者：
Shuang Gao;Zhipeng Bai;Shuang Liang;Hao Yu;Li Chen;Yanling Sun;Jian Mao;Hui Zhang;Zhenxing Ma;Merched Azzi;Hong Zhao
前体物浓度和气象条件对中国新出现的臭氧污染问题的作用受到广泛关注，特别是自2013年《大气污染防治与行动计划》（APPC）发布以来。随着PM2. 5在全国范围内呈下降趋势，由于影响臭氧形成的诸多因素之间存在复杂的非线性关系，严格的控制措施对臭氧变化的影响研究较少。利用KZ滤波和人工神经网络模型，分析了2013 - 2017年中国河北省两个城市和一个农村地区臭氧前体物和气象对最大日平均8 h臭氧（MDA 8）的影响。结果表明，以气象因子和前体物浓度作为人工神经网络模型的输入变量时，实测臭氧浓度与模拟的MDA 8臭氧浓度之间的R2为0.80。然而，人工神经网络模型在估计O3浓度峰值时存在局限性。在河北省3个监测点，MDA 8臭氧浓度的威胁值（TS）、检测概率（POD）和误报率（FAR）分别为39%、44%和21%。2014年至2017年，与臭氧相关的臭氧的年平均百分比变化为0. 67%。温度、大气压力和边界层高度是长期臭氧水平变化的64%。河北省臭氧变化主要由气象参数来再现，前体物浓度的贡献较小。
The role of precursors' concentrations and meteorological conditions on the emerging ozone pollution problem in China has received wide attention, especially after the releasing of the Air Pollution Prevention Control and Action Plan (APPC) since 2013. With the decreasing trend of PM2.5nationwide, the effect of the strict control measures on increasing ozone variation has less been studied due to the challenge of complexity of nonlinear relationship among a number of factors on ozone formation. This paper evaluated the influence of both ozone precursors and meteorology on maximum daily average 8 h (MDA8) ozone at two urban sites and one rural site in Hebei province, China, from 2013 to 2017, by using a combined application of Kolmogorov-Zurbenko (KZ) filter and artificial neural network (ANN) model. Results showed that R2was 0.80 between the measured and the simulated MDA8 ozone concentration when using meteorological factors and precursors' concentrations as input variables for ANN model. However, ANN model has limitation in estimating O3concentration peaks. The values of threat score (TS), probability of detection (POD) and false alarm rate (FAR) for MDA8 ozone concentration were 39%, 44% and 21%, respectively, throughout three studied sites in Hebei province. The annual average percentage change of precursor-related ozone was 0.67% from 2014 to 2017. Temperature, atmospheric pressure and boundary layer height were shown to account for 64% of the variability in long-term ozone levels. Ozone variation in Hebei province was reproduced mainly by meteorological parameters, and the contribution from precursors’ concentration was smaller during the years when the APPC was implemented.
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影响因子：
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发表时间：
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影响因子：
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