The earth’s surface ozone levels are becoming very significant due to their negative impact on human health, vegetation and climate. In this study, the methodology based on ensemble approach embodied linear and nonlinear behaviors was developed. It was applied for prediction of ozone concentration using dataset (2013–2016) of gaseous pollutants (O 3 , CO, NO x , MHC, TNMHCs) and meteorological variables as input variables. The daily O 3 max/O 3 min ratio of 10.9 marks the peculiar ozone pollution in the area. The fourteen prediction algorithms and their possible combinations of ensemble models were employed in this paper. Compared with individual models, the ensemble model approach showed an index of agreement of 0.91, the accuracy of 95.5% and mean absolute error of − 0.001 ppb between the predicted and observed diurnal cycle and daily averaged data of the year 2016 for benchmark analysis.

中文翻译：

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西北印度恒河平原地表臭氧综合评价与预测

由于对人类健康、植被和气候的负面影响，地球表面臭氧水平正变得非常重要。在这项研究中，开发了基于集成方法的方法，该方法体现了线性和非线性行为。它用于使用气态污染物（O 3 、CO、NO x 、MHC、TNMHCs）和气象变量作为输入变量的数据集（2013-2016）预测臭氧浓度。每日O 3 max/O 3 min 比值为10.9，标志着该地区特有的臭氧污染。本文采用了 14 种预测算法及其可能的集成模型组合。与单个模型相比，集成模型方法的一致性指数为 0.91，准确率为 95.5%，平均绝对误差为 − 0。