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Meteorological normalization of NO2 concentrations in the Province of Bolzano (Italian Alps)
Atmospheric Environment ( IF 4.2 ) Pub Date : 2021-02-01 , DOI: 10.1016/j.atmosenv.2020.118048
Marco Falocchi , Dino Zardi , Lorenzo Giovannini

Abstract Pollutant concentrations in the atmosphere are controlled not only by emissions, but also by meteorological processes. As a consequence, adverse atmospheric conditions may hinder the effects of policies intended to improve air quality through reduction of emissions. In particular, low ventilation conditions and temperature inversions may significantly inhibit pollutant transport and mixing, determining high concentrations close to the ground. In order to disentangle the contribution of weather conditions on observed pollutant concentrations, meteorological normalization techniques can be applied. In this study, a normalization procedure based on a random forest predictive model is applied to 8-year–long series of nitrogen dioxide (NO2) concentrations measured at five air quality stations in the Province of Bolzano (Italian Alps). The normalization is performed on daily–averages of NO2 concentrations, related to a dataset composed of time variables and meteorological data from seven weather stations and one temperature profiler. The strong dependence of observed NO2 concentrations on atmospheric variables (i.e. air temperature, atmospheric stability and wind speed) measured at the valley floor justifies the application of a normalization procedure. The resulting normalized time series of NO2 concentrations, instead, clearly display changes in correspondence of roadworks or other measures capable of modifying the emission regime, and allow to address the reliability of the applied procedure.

中文翻译:

博尔扎诺省(意大利阿尔卑斯山)二氧化氮浓度的气象标准化

摘要 大气中污染物的浓度不仅受排放的控制,还受气象过程的控制。因此,不利的大气条件可能会阻碍旨在通过减少排放来改善空气质量的政策的效果。特别是,低通风条件和逆温可能会显着抑制污染物的传输和混合,从而确定靠近地面的高浓度。为了弄清楚天气条件对观测到的污染物浓度的影响,可以应用气象归一化技术。在这项研究中,基于随机森林预测模型的归一化程序应用于在博尔扎诺省(意大利阿尔卑斯山)的五个空气质量站测量的为期 8 年的二氧化氮 (NO2) 浓度系列。标准化是对 NO2 浓度的日平均值进行的,该数据集与由来自七个气象站和一个温度剖面仪的时间变量和气象数据组成的数据集有关。观测到的 NO2 浓度对谷底测量的大气变量(即气温、大气稳定性和风速)的强烈依赖性证明了应用归一化程序是合理的。相反,由此产生的 NO2 浓度归一化时间序列清楚地显示了道路工程或其他能够修改排放制度的措施的对应变化,并允许解决应用程序的可靠性。与来自七个气象站和一个温度剖面仪的时间变量和气象数据组成的数据集相关。观测到的 NO2 浓度对谷底测量的大气变量(即气温、大气稳定性和风速)的强烈依赖性证明了应用归一化程序是合理的。相反,由此产生的 NO2 浓度归一化时间序列清楚地显示了道路工程或其他能够修改排放制度的措施的对应变化,并允许解决应用程序的可靠性。与来自七个气象站和一个温度剖面仪的时间变量和气象数据组成的数据集相关。观测到的 NO2 浓度对谷底测量的大气变量(即气温、大气稳定性和风速)的强烈依赖性证明了应用归一化程序是合理的。相反,由此产生的 NO2 浓度归一化时间序列清楚地显示了道路工程或其他能够修改排放制度的措施的对应变化,并允许解决应用程序的可靠性。
更新日期:2021-02-01
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