Daily maximum 8-h average (MDA8) ozone (O₃) concentrations are well-known to be influenced by local meteorological conditions, which vary across both daily and seasonal temporal scales. Previous studies have adjusted long-term trends in O₃ concentrations for meteorological effects using various statistical and mathematical methods in order to get a better estimate of the long-term changes in O₃ concentrations due to changes in precursor emissions such as nitrogen oxides (NO_X) and volatile organic compounds (VOCs). In this work, the authors present improvements to the current method used by the United States Environmental Protection Agency (US EPA) to adjust O₃ trends for meteorological influences by making refinements to the input data sources and by allowing the underlying statistical model to vary locally using a variable selection procedure. The current method is also expanded by using a quantile regression model to adjust trends in the 90th and 98th percentiles of the distribution of MDA8 O₃ concentrations, allowing for a better understanding of the effects of local meteorology on peak O₃ levels in addition to seasonal average concentrations. The revised method is used to adjust trends in the May to September mean, 90th percentile, and 98th percentile MDA8 O₃ concentrations at over 700 monitoring sites in the U.S. for years 2000–2016. The utilization of variable selection and quantile regression allow for a more in-depth understanding of how weather conditions affect O₃ levels in the U.S. This represents a fundamental advancement in our ability to understand how interannual variability in weather conditions in the U.S. may impact attainment of the O₃ National Ambient Air Quality Standards (NAAQS).

众所周知，每日最大 8 小时平均 (MDA8) 臭氧 (O ₃ ) 浓度受当地气象条件的影响，当地气象条件在每日和季节时间尺度上有所不同。_{以前的研究已经使用各种统计和数学方法调整了 O 3}浓度的长期趋势以获得气象影响，以便更好地估计由于前体排放物_（如氮氧化物（NO _X ) 和挥发性有机化合物 (VOC)。在这项工作中，作者提出了对美国环境保护署 (US EPA) 用于调整 O _{3的当前方法的改进。}通过对输入数据源进行细化并通过使用变量选择程序允许基础统计模型在局部变化来确定气象影响的趋势。目前的方法还通过使用分位数回归模型来调整 MDA8 O ₃浓度分布的第 90 和第 98 个百分位数的趋势，从而更好地了解当地气象对 O ₃峰值水平的影响以及季节性平均浓度。修正后的方法用于调整 5 月至 9 月平均值、第 90 个百分位和第 98 个百分位 MDA8 O _3的趋势2000-2016 年美国 700 多个监测点的浓度。利用变量选择和分位数回归可以更深入地了解天气条件如何影响美国的 O ₃水平 这代表了我们理解美国天气条件的年际变化如何影响实现目标的能力的根本性进步O ₃国家环境空气质量标准 (NAAQS)。