Response of cross-correlations between high PM2.5 and O3 with increasing time scales to the COVID-19: different trends in BTH and PRD

Environ Monit Assess (2023) 195:609 https://doi.org/10.1007/s10661-023-11213-w RESEARCH Response of cross‑correlations between high PM2.5 and O3 with increasing time scales to the COVID‑19: different trends in BTH and PRD Bingyi Bao · Youping Li · Chunqiong Liu · Ye Wen · Kai Shi Received: 7 September 2022 / Accepted: 3 April 2023 © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2023 Abstract The air pollution in China currently is characterized by high fine particulate matter (PM2.5) and ozone (O3) concentrations. Compared with single high pollution events, such double high pollution (DHP) events (both P M2.5 and O3 are above the National Ambient Air Quality Standards (NAAQS)) pose a greater threat to public health and environment. In 2020, the outbreak of COVID-19 provided a special time window to further understand the cross-correlation between PM2.5 and O3. Based on this background, a novel detrended cross-correlation analysis (DCCA) based on maximum time series of variable time scales (VM-DCCA) method is established in this paper to compare the cross-correlation The authors Chunqiong Liu and Kai Shi contributed equally to this work. B. Bao · Y. Wen College of Mathematics and Statistics, Jishou University, Jishou, Hunan, China e-mail: Y. Wen e-mail: Y. Li · C. Liu (*) · K. Shi (*) College of Environmental Science and Engineering, China West Normal University, Nanchong, Sichuan, China e-mail: K. Shi e-mail: Y. Li e-mail: between high PM2.5 and O3 in Beijing-Tianjin-Heibei (BTH) and Pearl River Delta (PRD). At first, the results show that PM2.5 decreased while O 3 increased in most cities due to the effect of COVID-19, and the increase in O3 is more significant in PRD than in BTH. Secondly, through DCCA, the results show that the PM2.5-O3 DCCA exponents α decrease by an average of 4.40% and 2.35% in BTH and PRD respectively during COVID-19 period compared with nonCOVID-19 period. Further, through VM-DCCA, the results show that the P M2.5-O3 VM-DCCA exponents 𝛼VM in PRD weaken rapidly with the increase of time scales, with decline range of about 23.53% and 22.90% during the non-COVID-19 period and COVID-19 period respectively at 28-h time scale. BTH is completely different. Without significant tendency, its 𝛼VM is always higher than that in PRD at different time scales. Finally, we explain the above results with the self-organized criticality (SOC) theory. The impact of meteorological conditions and atmospheric oxidation capacity (AOC) variation during the COVID-19 period on SOC state are further discussed. The results show that the characteristics of cross-correlation between high PM2.5 and O3 are the manifestation of the SOC theory of atmospheric system. Relevant conclusions are important for the establishment of regionally targeted PM2.5-O3 DHP coordinated control strategies. Keywords PM2.5-O3 DHP · Time scale · VM-DCCA· Long-term persistence · SOC Vol.: (0123456789) 13 609 Page 2 of 13 Introduction Despite the pollutant emissions that have been witnessed significant reduction in recent years, there are still heavy fine particulate matter (PM2.5) and ozone (O3) pollution events in some regions of China (Chen et al., 2022; Qin et al., 2021). Qin et al. (2021) reported that the occurrence of PM2.5-O3 double high pollution (DHP) events in China’s major city clusters were driven by a combination of the emissions of pollution sources and regional meteorological factors. It clearly implies that an enhanced understanding of the cross-correlation between high P M2.5 and O 3 in a city area has a primary significance to formulating regional targeted PM2.5-O3 DHP coordinated control strategies. PM2.5 and O3 not only have common precursors nitrogen dioxides (NOx) and volatile organic compounds (VOCs), but also interact with each other through a variety of atmospheric photochemical pathways, causing extremely complex non-linear responses (Chen et al., 2019a; Ding et al., 2013; Liu et al., 2023; Wu et al., 2021b). Firstly, PM2.5 can influence the formation and thickness of cloud by acting as a cloud condensation nuclei and enhance atmospheric extinction capacity to alter the photolysis rate, thus indirectly affect the formation of O3. For instance, Zhu et al. (2019) discovered the strong negative correlation between PM2.5 and O3 in northern China in winter, due to the influence of P M2.5 on photolysis rate. Chu et al. (2020) also reported that the increase in actinic flux owing to the reduction of air particles, leads to the rising of O 3 levels in China. Secondly, O3 can enhance the atmospheric oxidation capacity and thus produce photochemical oxidants such as hydroxyl (·OH) radicals, hydrogen peroxide (H2O2) and aldehyde (R-CHO). These oxidants can result in the rapid nucleation of secondary aerosol particles and boost the explosive growth of PM2.5. For instance, Jia et al. (2017) analyzed the interaction between PM2.5 and O 3 in Nanjing in different seasons and found that high O 3 levels in hot season could accelerate the formation of secondary particles. Fu et al. (2020) revealed that atmospheric oxidizing capacity enhanced by high O3 levels, played a key role in the conversion efficiency of NOx into nitrate (the main component of PM2.5 in North China Plain). At last, some other studies highlighted that the heterogeneous reactions of chemicals on particle surface Vol:. (1234567890) 13 Environ Monit Assess (2023) 195:609 also affect the formation and consumption of O 3 (Qu et al., 2018; Xu et al., 2012). Thus, the complexity of the interaction mechanism between PM2.5 and O3 and the effectiveness of P M2.5-O3 DHP coordinated control in city clusters are closely linked. Due to the temporal variability of meteorology and pollution emissions, the time scale dependence can be observed in the dominant mechanism of the cross-correlation between PM2.5 and O3. The photochemical mechanism by which photochemical oxidants such as O3 contribute to the rapid nucleation of secondary aerosol particles occurs mainly on the time scale of seconds to hours. For example, Wang et al. (2014) found that the explosive growth of PM2.5 levels in Beijing-Tianjin-Heibei mainly occurred at the time scale of several hours. At the same time, the photochemical mechanism by which particulate matter affects O 3 formation by scattering solar radiation occurs on daily, weekly, monthly and even longer time scales. For example, Xing et al. (2017) studied the impact of aerosol direct effects (ADEs) on tropospheric O3 in China and found that ADEs led to a decrease in the average O3 concentrations at time scale up to 1 month. In addition, the correlation between PM2.5 and O3 is also affected by the selection of research period. For example, Zhao et al. (2018) pointed out that the PM2.5 was positively correlated with the daily maximum of O3 at a 3-month scale in summer (from June to August 2016) and negatively correlated with it at a 3-month scale in winter (...truncated)