Chinese Regulations Are Working—Why Is Surface Ozone Over Industrialized Areas Still High? Applying Lessons From Northeast US Air Quality Evolution

Chen, Xiaokang; Jiang, Zhe; Shen, Yanan; Li, Rui; Fu, Yunfei; Liu, Jane; Han, Han; Liao, Hong; Cheng, Xugeng; Jones, Dylan B. A.; Worden, H. M.; Abad, G. González

doi:10.1029/2021gl092816

Cited by 65 publications

(43 citation statements)

References 51 publications

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“…Sicard, et al [ 38 ] reported that the lockdown during COVID-19 caused a substantial decrease in NO x (~ 56%) and an increase in O 3 (~ 36%) in Wuhan. Chen, et al [ 42 ] compared ozone pollution in China with ozone pollution in the USA in the 1990s and concluded that stricter NOx controls can improve O 3 pollutions over industrialized areas. In the abatement scenario of COVID-19, the Anhui region has not reached a NOx sensitive area.…”

Section: Resultsmentioning

confidence: 99%

A potential controlling approach on surface ozone pollution based upon power big data

Wang

et al. 2022

SN Appl. Sci.

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Surface ozone pollution has attracted extensive attention with the decreasing of haze pollution, especially in China. However, it is still difficult to efficiently control the pollution in time despite numbers of reports on mechanism of ozone pollution. Here we report a method for implementing effective control of ozone pollution through power big data. Combining the observation of surface ozone, NO2, meteorological parameters together with hourly electricity consumption data from volatile organic compounds (VOCs) emitting companies, a generalized additive model (GAM) is established for quantifying the influencing factors on the temporal and spatial distribution of surface ozone pollution from 2020 to 2021 in Anhui province, central China. The average R2 value for the modelling results of 16 cities is 0.82, indicating that the GAM model effectively captures the characteristics of ozone. The model quantifies the contribution of input variables to ozone, with both NO2 and industrial VOCs being the main contributors to ozone, contributing 33.72% and 21.12% to ozone formation respectively. Further analysis suggested the negative correlation between ozone and NO2, revealing VOCs primarily control the increase in ozone. Under scenarios controlling for a 10% and 20% reduction in electricity use in VOC-electricity sensitive industries that can be identified by power big data, ozone concentrations decreased by 9.7% and 19.1% during the pollution period. This study suggests a huge potential for controlling ozone pollution through power big data and offers specific control pathways.

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Section: Resultsmentioning

confidence: 99%

A potential controlling approach on surface ozone pollution based upon power big data

Wang

et al. 2022

SN Appl. Sci.

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“…The model configurations in this work are similar with Chen et al (2021), who have demonstrated the capability of this model to simulate surface O 3 concentrations in E. China. We refer the reader to Chen et al (2021) for the details of model configurations. The modeled NO 2 to be compared with satellite measurements (y trop ) are smoothed with OMI averaging kernels with the following approach (Huang et al 2014, Qu et al 2020):…”

Section: Geos-chem Model Simulationsmentioning

confidence: 65%

“…Regional emissions are replaced by Multiresolution Emission Inventory for China in China, and MIX in other regions of Asia (Li et al 2017). The model configurations in this work are similar with Chen et al (2021), who have demonstrated the capability of this model to simulate surface O 3 concentrations in E. China. We refer the reader to Chen et al (2021) for the details of model configurations.…”

Section: Geos-chem Model Simulationsmentioning

confidence: 82%

Large discrepancy between observed and modeled wintertime tropospheric NO₂ variabilities due to COVID-19 controls in China

Chen

Jiang

Liao

et al. 2022

Environ. Res. Lett.

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Recent studies demonstrated the difficulties to explain observed tropospheric nitrogen dioxide (NO2) variabilities over the United States (US) and Europe, but thorough analysis for the impacts on tropospheric NO2 in China is still lacking. Here we provide a comparative analysis for the observed and modeled (GEOS-Chem) tropospheric NO2 in early 2020 in China. Both Ozone Monitoring Instrument (OMI) and surface NO2 measurements show marked decreases in NO2 abundances due to the 2019 novel coronavirus (COVID-19) controls. However, we find a large discrepancy between observed and modeled NO2 changes over highly polluted provinces: the observed reductions in tropospheric NO2 columns are about 40% lower than those in surface NO2 concentrations. By contrast, the modeled reductions in tropospheric NO2 columns are about 2 times higher than those in surface NO2 concentrations. This discrepancy could be driven by the combined effects from uncertainties in simulations and observations, associated with possible inaccurate simulations of lower tropospheric NO2, larger uncertainties in the modeled interannual variabilities of NO2 columns, as well as insufficient consideration of aerosol effects and a priori NO2 variability in satellite retrievals. In addition, our analysis suggests a small influence from free tropospheric NO2 backgrounds in E. China in winter. This work demonstrates the challenge to interpret wintertime tropospheric NO2 changes in China, highlighting the importance of integrating surface NO2 observations to provide better analysis for NO2 variabilities.

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“…As shown in Figure 5, the NO 2 concentration clearly demonstrates a continuous decreasing trend over the YRD region during 2014-2020. In term of VOCs, we employed the column density of HCHO via satellite retrievals to represent the interannual variations of VOCs (Li R. et al, 2021). The column density of HCHO shows an inverted "U" shape, which increases from 7.2 × 10 15 molec cm 2 (2014) to 8.0 × 10 15 molec•cm 2 (2017) and then drops to 7.4 × 10 15 molec cm 2 (2020).…”

Section: Driving Factors Of Interannual Changes In O 3 From 2014 To 2020mentioning

confidence: 99%

“…However, the upward trend has significant differences in different regions and different periods. Chen et al (2021) revealed that annual O 3 concentration was in continuous increase across the YRD region during 2014-2019 but rose in volatility in the Pearl River Delta (PRD) region over the same period. In addition, the increment of O 3 in the YRD region is more obvious with a rate of 3.2 ppbv yr −1 from 50.7 to 66.3 ppbv, which is approximately four times that in the PRD region.…”

Section: Introductionmentioning

confidence: 99%

Increasing but Variable Trend of Surface Ozone in the Yangtze River Delta Region of China

Tang

Zhang

Feng

et al. 2022

Front. Environ. Sci.

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Surface ozone (O3) increased by ∼20% in the Yangtze River Delta (YRD) region of China during 2014–2020, but the aggravating trend is highly variable on interannual time and city-level space scales. Here, we employed multiple air quality observations and numerical simulation to describe the increasing but variable trend of O3 and to reveal the main driving factors behind it. In 2014–2017, the governmental air pollution control action plan was mostly against PM2.5 (mainly to control the emissions of SO2, NOx, and primary PM2.5) and effectively reduced the PM2.5 concentration by 18%–45%. However, O3 pollution worsened in the same period with an increasing rate of 4.9 μg m−3 yr−1, especially in the Anhui province, where the growth rate even reached 14.7 μg m−3 yr−1. After 2018, owing to the coordinated prevention and control of both PM2.5 and O3, volatile organic compound (VOC) emissions in the YRD region has also been controlled with a great concern, and the O3 aggravating trend in the same period has been obviously alleviated (1.1 μg m−3 yr−1). We further combined the precursor concentration and the corresponding O3 formation regime to explain the observed trend of O3 in 2014–2020. The leading O3 formation regime in 2014–2017 is diagnosed as VOC-limited (21%) or mix-limited (58%), with the help of a simulated indicator HCHO/NOy. Under such condition, the decreasing NO2 (2.8% yr−1) and increasing VOCs (3.6% yr−1) in 2014–2017 led to a rapid increment of O3. With the continuous reduction in NOx emission and further in ambient NOx/VOCs, the O3 production regime along the Yangtze River has been shifting from VOC-limited to mix-limited, and after 2018, the mix-limited regime has become the dominant O3 formation regime for 55% of the YRD cities. Consequently, the decreases of both NOx (3.3% yr−1) and VOCs (7.7% yr−1) in 2018–2020 obviously slowed down the aggravating trend of O3. Our study argues that with the implementation of coordinated regional reduction of NOx and VOCs, an effective O3 control is emerging in the YRD region.

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Chinese Regulations Are Working—Why Is Surface Ozone Over Industrialized Areas Still High? Applying Lessons From Northeast US Air Quality Evolution

Cited by 65 publications

References 51 publications

A potential controlling approach on surface ozone pollution based upon power big data

A potential controlling approach on surface ozone pollution based upon power big data

Large discrepancy between observed and modeled wintertime tropospheric NO₂ variabilities due to COVID-19 controls in China

Increasing but Variable Trend of Surface Ozone in the Yangtze River Delta Region of China

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Chinese Regulations Are Working—Why Is Surface Ozone Over Industrialized Areas Still High? Applying Lessons From Northeast US Air Quality Evolution

Cited by 65 publications

References 51 publications

A potential controlling approach on surface ozone pollution based upon power big data

A potential controlling approach on surface ozone pollution based upon power big data

Large discrepancy between observed and modeled wintertime tropospheric NO2 variabilities due to COVID-19 controls in China

Increasing but Variable Trend of Surface Ozone in the Yangtze River Delta Region of China

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Large discrepancy between observed and modeled wintertime tropospheric NO₂ variabilities due to COVID-19 controls in China