Long-term trends of ozone and precursors from 2013 to 2020 in a megacity (Chengdu), China: Evidence of changing emissions and chemistry

Wang, Yurun; Yang, Xiangdong; Wu, Kai; Han, Min−Koo; Smedt, Isabelle De; Wang, Shigong; Fan, Jin; Lyu, Shihua; He, Cheng

doi:10.1016/j.atmosres.2022.106309

Cited by 17 publications

(6 citation statements)

References 56 publications

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“…For NO 2 , the response value of O 3 pollution to NO 2 in the main region of the YRD decreased from 2011 to 2016, reached a minimum value in 2016, and then increased from 2016 to 2020. This may be related to the negative feedback of O 3 pollution on NO 2 [64,65]. The NO 2 concentration (shown in Figure S8) in 2011-2012 in northeastern YRD was relatively lower than that in 2010, and the response value of O 3 to NO 2 in 2011-2012 was positive, while NO 2 concentration in 2011-2012 in the central part of the YRD was higher, so the response value of O 3 to NO 2 in 2011-2012 was negative in this region.…”

Section: Pm 25 and O 3 Collaborative Pollution Response To Each Precu...mentioning

confidence: 99%

Quantitative Estimation of the Impacts of Precursor Emissions on Surface O3 and PM2.5 Collaborative Pollution in Three Typical Regions of China via Multi-Task Learning

Liu,

Ma,

Liu

et al. 2024

Sustainability

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The coordinated control of PM2.5 and O3 pollution has become a critical factor restricting the improvement of air quality in China. In this work, precursors and related influencing factors were utilized to establish PM2.5 and O3 estimation models in the North China Plain (NCP), the Yangzi River Delta (YRD), and the Pearl River Delta (PRD) using a multi-task-learning (MTL) model. The prediction accuracy of these three MTL models was high, with R2 values ranging from 0.69 to 0.83. Subsequently, these MTL models were used to quantitatively reveal the relative importance of each factor to PM2.5 and O3 collaborative pollution simultaneously. Precursors and meteorological factors were the two most critical influencing factors for PM2.5 and O3 pollution in three regions, with their relative importance values larger than 29.99% and 15.89%, respectively. Furthermore, these models were used to reveal the response of PM2.5 and O3 to each precursor in each region. In the NCP and the YRD, the two most important precursors of PM2.5 pollution are SO2 and HCHO, while the two most critical factors for O3 pollution are HCHO and NO2. Therefore, SO2 and VOC emissions reduction is the most important measure for PM2.5 pollution, while VOC and NO2 emission reduction is the most critical measure for O3 pollution in these two regions. In terms of the PRD, SO2 and NO2 are the most important precursors of PM2.5 pollution, while the most important precursors for O3 pollution are HCHO and SOX, respectively. Thus, NO2, SO2, and VOC emission reduction is the most critical measure for PM2.5 pollution, while VOC and NO2 emission reduction is the most critical measure for O3 pollution in the PRD. Overall, this study provides clues and references for the control of PM2.5 and O3 collaborative pollution in the NCP, the YRD, and the PRD.

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Section: Pm 25 and O 3 Collaborative Pollution Response To Each Precu...mentioning

confidence: 99%

Quantitative Estimation of the Impacts of Precursor Emissions on Surface O3 and PM2.5 Collaborative Pollution in Three Typical Regions of China via Multi-Task Learning

Liu,

Ma,

Liu

et al. 2024

Sustainability

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“…It achieves a spectral resolution of 0.55 nm in the 328–359 nm band range where HCHO retrieval is performed. We use 2019–2022 TROPOMI HCHO tropospheric vertical column product (De Smedt et al., 2018), which has been thoroughly validated (Chan et al., 2020; De Smedt et al., 2018; Vigouroux et al., 2020) and used to study NMVOC emissions (Pu et al., 2022; Sun et al., 2021; Wang et al., 2022). To ensure data quality, we select level 2 pixels with quality assurance value greater than 0.5, cloud fraction less than 0.3, and solar zenith angle less than 60°.…”

Section: Tropomi Hcho Columns and Wind Rotation Approachmentioning

confidence: 99%

Observing Downwind Structures of Urban HCHO Plumes From Space: Implications to Non‐Methane Volatile Organic Compound Emissions

Zuo,

Sun,

De Smedt

et al. 2023

Geophysical Research Letters

Self Cite

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Non‐methane volatile organic compounds (NMVOCs) have a significant impact on air quality in urban areas. Detecting NMVOCs emission with its proxy HCHO on urban scales from space, however, has been limited by the lack of discernible enhancement. Here we show clear urban HCHO plumes from 16 cities over the globe by rotating TROPOspheric Monitoring Instrument HCHO pixels according to wind directions. We fit the downwind structure of the plumes with the exponentially modified Gaussian approach to quantify urban HCHO effective production rates between 7.0 and 88.5 mol s−1. Our results are in line with total NMVOC emissions from the EDGAR inventory (r = 0.76). Our work offers a new measure of total NMVOC emissions from urban areas and highlights the potential of satellite HCHO data to provide new information for monitoring urban air quality.

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“…It achieves a spectral resolution of 0.55 nm in the 328-359 nm band range where HCHO retrieval is performed. We use 2019-2022 TROPOMI HCHO tropospheric vertical column product (De Smedt et al, 2018), which has been thoroughly validated (Chan et al, 2020;De Smedt et al, 2018;Vigouroux et al, 2020) and used to study NMVOC emissions (Pu et al, 2022;Sun et al, 2021;Wang et al, 2022). To ensure data quality, we select level 2 pixels with quality assurance (QA) value greater than 0.5, cloud fraction less than 0.3, and solar zenith angle less than 60º .…”

Section: Tropomi Hcho Columns and Wind Rotation Approachmentioning

confidence: 99%

Observing downwind structures of urban HCHO plumes from space: Implications to non-methane volatile organic compound emissions

Zuo,

Sun,

Smedt

et al. 2023

Preprint

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Non-methane volatile organic compounds (NMVOCs) have a significant impact on air quality in urban areas. Detecting NMVOCs emission with its proxy HCHO on urban scales from space, however, has been limited by the lack of discernible enhancement. Here we show clear urban HCHO plumes from 11 cities over the globe by rotating TROPOspheric Monitoring Instrument (TROPOMI) HCHO pixels according to wind directions. We fit the downwind structure of the plumes with the exponentially modified Gaussian (EMG) approach to quantify urban HCHO effective production rates between 22.7 mol s-1 and 115.8 mol s-1. Our results are in line with estimations using the EDGAR inventory (r = 0.81). Our work offers a new way of constraining NMVOC emissions from urban areas and highlights the potential of satellite HCHO data to provide new information for monitoring urban air quality.

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Long-term trends of ozone and precursors from 2013 to 2020 in a megacity (Chengdu), China: Evidence of changing emissions and chemistry

Cited by 17 publications

References 56 publications

Quantitative Estimation of the Impacts of Precursor Emissions on Surface O3 and PM2.5 Collaborative Pollution in Three Typical Regions of China via Multi-Task Learning

Quantitative Estimation of the Impacts of Precursor Emissions on Surface O3 and PM2.5 Collaborative Pollution in Three Typical Regions of China via Multi-Task Learning

Observing Downwind Structures of Urban HCHO Plumes From Space: Implications to Non‐Methane Volatile Organic Compound Emissions

Observing downwind structures of urban HCHO plumes from space: Implications to non-methane volatile organic compound emissions

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