Abstract
The formation of ground-level ozone (O3) is dependent on both atmospheric chemical processes and meteorological factors. Traditional models have difficulty assessing O3 formation sensitivity in a timely manner due to the limitations of flexibility and computational efficiency. In this study, a random forest (RF) model coupled with the reactivity of volatile organic compound (VOC) species was used to investigate the O3 formation sensitivity in Beijing from 2014 to 2016, and evaluate the relative importance (RI) of chemical and meteorological factors to O3 formation. The results showed that the O3 prediction performance using initial concentrations of VOC species (R2 = 0.87) was better than that using total VOCs (TVOCs) concentrations (R2 = 0.77). Meanwhile, the RIs of VOC species correlated well with their O3 formation potentials (OFPs). O3 formation presented a negative response to NOx, PM2.5 and relative humidity, and a positive response to temperature, solar radiation and VOCs. The O3 isopleth curves calculated by the RF model were generally comparable with those calculated by the box model. O3 formation shifted from a VOC-limited regime to a transition regime from 2014 to 2016. This study demonstrates that the RF model coupled with the initial concentrations of VOC species could provide an accurate, flexible, and computationally efficient approach for O3 sensitivity analysis.
Highlights
The O3-volatile organic compound (VOC)-NOx sensitivity is readily influenced by volatile organic compounds (VOCs) species (Tan et al, 2018), meteorological parameters (Liu et al, 2020a; Liu & Wang 2020), and even atmospheric particulate matter (Li et al, 2019), exhibits high temporal and spatial variability
Our study indicates that the random forest (RF) model combined with initial concentrations of VOC species can simulate O3 concentrations well and provides a flexible and efficient tool for O3 modelling in a near real-time way
2014-2016 in Beijing using the RF model coupled with the reactivity of VOC species
Summary
Ground-level ozone (O3) pollution, which can cause adverse human health effects such as cardiovascular and respiratory diseases, has received increasing attention in recent decades (Cohen et al, 2017). As important precursors of O3, volatile organic compounds (VOCs) in the atmosphere are oxidized to produce peroxyl radicals (RO2). The production and loss of RO2 and HO2 are highly dependent on the concentration ratio of VOCs and NOx in the atmosphere. Atmospheric O3 concentrations or production rates show a nonlinear relationship with VOCs and NOx. the O3-VOC-NOx sensitivity is readily influenced by VOC species (Tan et al, 2018), meteorological parameters (Liu et al, 2020a; Liu & Wang 2020), and even atmospheric particulate matter (Li et al., 2019), exhibits high temporal and spatial variability. It is urgent to develop an accurate and highly efficient method for timely assessing the sensitivity regime of O3 production and evaluating the effectiveness of a potential measure on O3 pollution control
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