Changes in first- and second-order sensitivities of ozone concentration to its precursors over the Yangtze River Delta region of China due to COVID-19 lockdown: Insights from CMAQ-HDDM modeling study

Yaluk, Elly; Wang, Yangjun; Jiang, Sen; Lu, Guibin; Zhu, Aimei; Bian, Jinting; Xue, Junmin; Du, Yufei; Chen, Nan; Manomaiphiboon, Kasemsan; Chen, H.; Zhang, Kun; Liu, Jinchu

doi:10.1016/j.atmosenv.2023.119931

Cited by 2 publications

(2 citation statements)

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“…A general conclusion is that ozone production is increased due to the reduction in NO x , with seasonal variation and spatial difference . Besides, O 3 formation regimes also change due to the noncoordinated reduction in the NO x and volatile organic compounds (VOCs) emissions, , which also affects the secondary particle formation . However, in situ measurements are crucial to validate the emission pattern change and the subsequent oxidation.…”

Section: Introductionmentioning

confidence: 99%

Atmospheric Oxidation Capacity Elevated during 2020 Spring Lockdown in Chengdu, China: Lessons for Future Secondary Pollution Control

Tan,

Feng,

Liu

et al. 2024

Environ. Sci. Technol.

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This study presents the measurement of photochemical precursors during the lockdown period from January 23, 2020, to March 14, 2020, in Chengdu in response to the coronavirus (COVID-19) pandemic. To derive the lockdown impact on air quality, the observations are compared to the equivalent periods in the last 2 years. An observation-based model is used to investigate the atmospheric oxidation capacity change during lockdown. OH, HO2, and RO2 concentrations are simulated, which are elevated by 42, 220, and 277%, respectively, during the lockdown period, mainly due to the reduction in nitrogen oxides (NO x ). However, the radical turnover rates, i.e., OH oxidation rate L(OH) and local ozone production rate P(O3), which determine the secondary intermediates formation and O3 formation, only increase by 24 and 48%, respectively. Therefore, the oxidation capacity increases slightly during lockdown, which is partly attributed to unchanged alkene concentrations. During the lockdown, alkene ozonolysis seems to be a significant radical primary source due to the elevated O3 concentrations. This unique data set during the lockdown period highlights the importance of controlling alkene emission to mitigate secondary pollution formation in Chengdu and may also be applicable in other regions of China given an expected NO x reduction due to the rapid transformation to electrified fleets in the future.

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Section: Introductionmentioning

confidence: 99%

Atmospheric Oxidation Capacity Elevated during 2020 Spring Lockdown in Chengdu, China: Lessons for Future Secondary Pollution Control

Tan,

Feng,

Liu

et al. 2024

Environ. Sci. Technol.

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“…Ozone pollution is a complex and diverse process driven by the interaction of multiple factors rather than just a single factor. Moreover, the level of ozone pollution differs widely both temporally and spatially [9][10][11][12]. Previous studies have primarily focused on analyzing ozone levels based on seasonal-or annual-scale data, often lacking a thorough exploration and analysis of the spatial variations, especially the significant difference between urban and suburban areas [13][14][15][16][17][18].…”

Section: Introductionmentioning

confidence: 99%

Spatiotemporal Changes in and Forces Driving Ozone Concentration in the Beijing–Tianjin–Hebei (Jing–Jin–Ji) Region from 2015 to 2022

Xiong,

Liu,

et al. 2024

Atmosphere

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This study aims to explore the factors affecting variation in ozone concentration, using ozone concentration monitoring data from the Beijing–Tianjin–Hebei (Jing–Jin–Ji) region from 2015 to 2022. The characteristics of the spatial and temporal variation in ozone concentration, as well as the impact of meteorological and land-use types on this variation, were investigated. Seasonally, ozone concentrations in the Jing–Jin–Ji region were highest in summer, followed by spring and autumn, and were lowest in winter. Spatially, a characteristic trend of lower concentrations in urban centers and higher concentrations in suburban areas was found. From the results of correlation analysis and a stepwise regression model, temperature and solar radiation were found to be the primary factors affecting seasonal variations in ozone concentration, explaining 67.9% of the variance. Additionally, the results of geographically weighted regression models confirmed the spatial heterogeneity of the impact of temperature and solar radiation on ozone concentration. In urban centers, such as Beijing and Tianjin, temperature and solar radiation more strongly influenced ozone concentration. To determine the factors driving this spatial heterogeneity, a geodetector was employed to analyze the impact of various geographical factors on the spatial distribution of ozone concentration. In winter, the impact of various factors of urbanization, such as lighting index, population density, and construction land, as well as air quality factors (PM2.5 and NO2), on ozone concentration was stronger, with q values greater than 0.2. However, in autumn, the influence of these factors on ozone concentration weakened. Furthermore, the results of the two-factor interaction detection analysis showed that the q values for the interaction between urban and air quality factors ranged between 0.40 and 0.47, which were substantially higher than those for other interactions. This further confirmed the strong influence of urban activities on ozone concentration.

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Changes in first- and second-order sensitivities of ozone concentration to its precursors over the Yangtze River Delta region of China due to COVID-19 lockdown: Insights from CMAQ-HDDM modeling study

Cited by 2 publications

References 48 publications

Atmospheric Oxidation Capacity Elevated during 2020 Spring Lockdown in Chengdu, China: Lessons for Future Secondary Pollution Control

Atmospheric Oxidation Capacity Elevated during 2020 Spring Lockdown in Chengdu, China: Lessons for Future Secondary Pollution Control

Spatiotemporal Changes in and Forces Driving Ozone Concentration in the Beijing–Tianjin–Hebei (Jing–Jin–Ji) Region from 2015 to 2022

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