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Quantifying impacts of crop residue burning in the North China Plain on summertime tropospheric ozone over East Asia

机译:量化华北平原燃烧作物残渣对东亚夏季对流层臭氧的影响

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Crop residue burning has been proved to have negative impacts on regional atmospheric environment. In this study, an evidence-based statistical modeling framework was established to quantify potential impacts of crop residue burning in the North China Plain (NCP) on summertime tropospheric ozone increase over East Asia during 2004-2016. To assess the intensity of crop residue burning, fire occurrence counts derived from the MODerate-resolution Imaging Spectroradiometer onboard the Terra and Aqua satellites were used as a proxy. Additionally, another six factors were employed as potent explanatory variables. Maximum covariance analysis was first applied to decouple spatiotemporal interactions between tropospheric ozone and each explanatory variable. Based on the decoupled modes, multivariate linear regression (MLR) and artificial neural network (ANN) were used to establish statistical relationships between tropospheric ozone and contributing factors, respectively. The results indicate that the ANN-based modeling scheme enables to approximate the observed tropospheric ozone variations better than MLR. Further investigations reveal that the summertime crop residue burning in the NCP is the predominant factor contributing to the observed additive tropospheric ozone increases over East Asia, yielding extra 8% tropospheric ozone elevation on average in June. Moreover, UV radiation and wind also played critical roles in modulating the observed tropospheric ozone variations therein. In general, the critical role of crop residue burning over the NCP in modulating summertime tropospheric ozone increase over East Asia have been well demonstrated based on the proposed evidenced-based modeling framework.
机译:作物残渣燃烧已被证明对区域大气环境具有负面影响。在这项研究中,建立了一个基于证据的统计建模框架,以量化华北平原(NCP)作物残渣燃烧对2004-2016年东亚夏季对流层臭氧增加的潜在影响。为了评估农作物残渣燃烧的强度,使用了从Terra和Aqua卫星上的MODerate分辨率成像光谱仪获得的火灾发生次数作为代理。另外,另外六个因素被用作有效的解释变量。首先使用最大协方差分析来分离对流层臭氧与每个解释变量之间的时空相互作用。基于解耦模式,分别使用多元线性回归(MLR)和人工神经网络(ANN)建立对流层臭氧与影响因子之间的统计关系。结果表明,基于ANN的建模方案能够比MLR更好地估计对流层臭氧的变化。进一步的调查表明,NCP夏季作物残渣燃烧是导致东亚观测到的对流层臭氧增加的主要因素,6月平均增加了8%的对流层臭氧。此外,紫外线和风在调制其中观测到的对流层臭氧变化方面也起着关键作用。总体而言,基于拟议的基于证据的建模框架已充分证明了在NCP上燃烧作物残渣在调节东亚夏季对流层臭氧增加中的关键作用。

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