Summertime ozone pollution in Sichuan Basin, China: Meteorological conditions, sources and process analysis

Yang, Xiangdong; Wu, Kai; Wang, Haolin; Liu, Yiming; Gu, Shenyan; Lü, Yaqiong; Zhang, Xiaoling; Hu, Yishi; Ou, Yihan; Wang, Shigong; Wang, Zhanshan

doi:10.1016/j.atmosenv.2020.117392

Cited by 95 publications

(43 citation statements)

References 38 publications

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“…The surface ozone concentrations of eastern Sichuan and western Chongqing are higher than other parts in SCB. This may be caused by high temperature and low humidity [60]. Figure 15 shows the correlation of surface ozone concentrations with temperature and RH in eastern Sichuan and western Chongqing from 2018 to 2019.…”

Section: Discussionmentioning

confidence: 99%

Estimation of Lower-Stratosphere-to-Troposphere Ozone Profile Using Long Short-Term Memory (LSTM)

Zhang

Lu³

et al. 2021

Remote Sensing

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Climate change and air pollution are emerging topics due to their possible enormous implications for health and social perspectives. In recent years, tropospheric ozone has been recognized as an important greenhouse gas and pollutant that is detrimental to human health, agriculture, and natural ecosystems, and has shown a trend of increasing interest. Machine-learning-based approaches have been widely applied to the estimation of tropospheric ozone concentrations, but few studies have included tropospheric ozone profiles. This study aimed to predict the Northern Hemisphere distribution of Lower-Stratosphere-to-Troposphere (LST) ozone at a pressure of 100 hPa to the near surface by employing a deep learning Long Short-Term Memory (LSTM) model. We referred to a history of all the observed parameters (meteorological data of European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis v5 (ERA5), satellite data, and the ozone profiles of the World Ozone and Ultraviolet Data Center (WOUDC)) between 2014 and 2018 for training the predictive models. Model–measurement comparisons for the monitoring sites of WOUDC for the period 2019–2020 show that the mean correlation coefficients (R2) in the Northern Hemisphere at high latitude (NH), Northern Hemisphere at middle latitude (NM), and Northern Hemisphere at low latitude (NL) are 0.928, 0.885, and 0.590, respectively, indicating reasonable performance for the LSTM forecasting model. To improve the performance of the model, we applied the LSTM migration models to the Civil Aircraft for the Regular Investigation of the Atmosphere Based on an Instrument Container (CARIBIC) flights in the Northern Hemisphere from 2018 to 2019 and three urban agglomerations (the Sichuan Basin (SCB), North China Plain (NCP), and Yangtze River Delta region (YRD)) between 2018 and 2019. The results show that our models performed well on the CARIBIC data set, with a high R2 equal to 0.754. The daily and monthly surface ozone concentrations for 2018–2019 in the three urban agglomerations were estimated from meteorological and ancillary variables. Our results suggest that the LSTM models can accurately estimate the monthly surface ozone concentrations in the three clusters, with relatively high coefficients of 0.815–0.889, root mean square errors (RMSEs) of 7.769–8.729 ppb, and mean absolute errors (MAEs) of 6.111–6.930 ppb. The daily scale performance was not as high as the monthly scale performance, with the accuracy of R2 = 0.636~0.737, RMSE = 14.543–16.916 ppb, MAE = 11.130–12.687 ppb. In general, the trained module based on LSTM is robust and can capture the variation of the atmospheric ozone distribution. Moreover, it also contributes to our understanding of the mechanism of air pollution, especially increasing our comprehension of pollutant areas.

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Section: Discussionmentioning

confidence: 99%

Estimation of Lower-Stratosphere-to-Troposphere Ozone Profile Using Long Short-Term Memory (LSTM)

Zhang

Lu³

et al. 2021

Remote Sensing

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“…The formation of O 3 in ambient atmosphere is facilitated during the summer season due to the presence of sufficient sunlight for photochemical reaction as given below in Equation 1 . 25 , 26 …”

Section: Discussionmentioning

confidence: 99%

Air Quality Before and After COVID-19 Lockdown Phases Around New Delhi, India

Chaudhary

Kumar

Antil

et al. 2021

Journal of Health and Pollution

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“…The national biogenic emission inventory has shown that the BVOC emissions in the PRD are much higher than those in the NCP and YRD regions (Li et al., 2012; Wang et al., 2020; Wu et al., 2020). Despite large biogenic VOC emissions around the PRD, the impacts of biogenic emissions on ground‐level O 3 pollution in PRD, with dense vegetation cover, have not been well quantified (Ou et al., 2016; Tan et al., 2018; Yang et al., 2020). Furthermore, the assessment of the effects of HW‐induced BVOC enhancements in regional O 3 episodes over PRD has received less attention.…”

Section: Introductionmentioning

confidence: 99%

Role of Heat Wave‐Induced Biogenic VOC Enhancements in Persistent Ozone Episodes Formation in Pearl River Delta

Wang

Liu

et al. 2021

JGR Atmospheres

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Regional ozone (O3) pollution is influenced by a combination of anthropogenic sources and biogenic volatile organic compounds (BVOC) emitted from vegetation. Under the influence of warming climate and projected expansion of urban green space, O3 pollution may get worse, especially during heat waves (HWs). However, HW‐induced changes in BVOC and subsequent effects on regional O3 pollution have not been adequately assessed. In this study, we used the Weather Research and Forecasting‐Community Multi‐scale Air Quality models to investigate the formation of a typical O3 episode and quantify the O3 response to BVOC in the Pearl River Delta during a HW in 2017. The results showed that the rate of increase of O3 during the HW was 27.1 µg m−3 °C−1, reflecting the rapid O3 formation under high temperature. Compared with the non‐HW (NHW), gas‐phase chemistry and vertical transport were dominant contributors to O3 formation. Sensitivity experiments indicate that the contribution of BVOC to ground‐level O3 formation in Pearl River Delta was up to 42.1 μg m−3 because BVOC emissions in HW were 430 mol d−1 higher than the NHW. Under northerly winds and strong sea‐land breezes, BVOC and oxidation products from rural areas were transported to downwind VOC‐limited regimes and result in severe O3 pollution owing to intense photochemical reactions and accumulated O3 precursors. These findings point to the essential role of BVOC enhancements induced by HWs to O3 formation and suggest the consideration of BVOC emission potential of planted trees in urban greening strategies for avoiding the offset effects from BVOC.

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Summertime ozone pollution in Sichuan Basin, China: Meteorological conditions, sources and process analysis

Cited by 95 publications

References 38 publications

Estimation of Lower-Stratosphere-to-Troposphere Ozone Profile Using Long Short-Term Memory (LSTM)

Estimation of Lower-Stratosphere-to-Troposphere Ozone Profile Using Long Short-Term Memory (LSTM)

Air Quality Before and After COVID-19 Lockdown Phases Around New Delhi, India

Role of Heat Wave‐Induced Biogenic VOC Enhancements in Persistent Ozone Episodes Formation in Pearl River Delta

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