Sensitivity of isoprene emission rate to ozone in greening trees is concurrently determined by isoprene synthesis capacity and stomatal conductance

Li, Shuangjiang; Agathokleous, Evgenios; Li, Shenglan; Yuan, Xiangyang; Du, Ye; Zhu, Feng

doi:10.1016/j.scitotenv.2023.164325

Cited by 3 publications

(2 citation statements)

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“…Except for the established influences of ozone precursors and weather elements, the NDVI has also been acknowledged as playing a significant role in ozone pollution. This effect is thought to result from the increased release of bioisoprene from plants, which subsequently leads to higher ozone concentrations [42,43]. Furthermore, the DEM, LULC, and POPU have been identified as influential factors in surface ozone pollution [42,44,45].…”

Section: The Relative Importance Of Explanatory Variables To O 3 Poll...mentioning

confidence: 99%

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Quantitative Analysis of Spatiotemporal Patterns and Factor Contributions of Surface Ozone in the North China Plain

Li,

Liu,

et al. 2024

Applied Sciences

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Over the past decade, surface ozone has emerged as a significant air pollutant in China, especially in the North China Plain (NCP). For effective ozone management in the NCP, it is crucial to accurately estimate the surface ozone levels and identify the primary influencing factors for ozone pollution in this region. This study utilized ozone precursors such as volatile organic compounds (VOCs) and nitrogen oxides (NOX), meteorological data, land cover, normalized difference vegetation index (NDVI), terrain, and population data to build an extreme gradient boosting (XGBoost)-based ozone estimation model in the NCP during 2019 to 2021. Four ozone estimation models were developed using different NO2 and formaldehyde (HCHO) datasets from the Sentinel-5 TROPOMI observations and Copernicus Atmosphere Monitoring Service (CAMS) reanalysis data. Site-based validation results of these four models showed high accuracy with R2 values above 0.86. Among these four models, two models with higher accuracy and higher spatial coverage ratio were selected, and their results were averaged to produce the final ozone estimation products. The results indicated that VOCs and NOX were the two main pollutants causing ozone pollution in the NCP, and their relative contributions accounted for more than 23.34% and 10.23%, respectively, while HCHO also played a significant role, contributing over 5.64%. Additionally, meteorological factors also had a notable impact, contributing 28.63% to ozone pollution, with each individual factor contributing more than 2.38%. The spatial distribution of ozone pollution identified the Hebei–Shandong–Henan junction as a pollution hotspot, with the peak occurring in summer, particularly in June. Therefore, for this hotspot region in the NCP, promoting the reduction in VOCs and NOx can play an important role in the mitigation of O3 pollution and the improvement in air quality in this region.

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Section: The Relative Importance Of Explanatory Variables To O 3 Poll...mentioning

confidence: 99%

“…This effect is thought to result from the increased release of bioisoprene from plants, which subsequently leads to higher ozone concentrations [42,43]. Furthermore, the DEM, LULC, and POPU have been identified as influential factors in surface ozone pollution [42,44,45].…”

Section: The Relative Importance Of Explanatory Variables To O 3 Poll...mentioning

confidence: 99%