Spatiotemporal trends and impact factors of PM&amp;lt;sub&amp;gt;2.5&amp;lt;/sub&amp;gt; and O&amp;lt;sub&amp;gt;3&amp;lt;/sub&amp;gt; pollution in major cities in China during 2015&amp;ndash;2020

Zhang, Yunjiang; Lei, Ruoyuan; Cui, Shijie; Wang, Hongli; Chen, Mindong; Gai, Xinlei

doi:10.1360/tb-2021-0767

Cited by 10 publications

(3 citation statements)

References 67 publications

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“…Biomass and coal have been extensively used for heating purposes in rural areas (Zhang et al., 2020). The combustion of biomass and coal releases substantial amounts of SO 2 , NO X , CO, and PM into the ambient air, contributing to severe air pollution in northern China (Yun et al., 2020; Zhang et al., 2021). Apart from SO 2 , the deweathered CO, NO 2 , and PM time series also exhibit a dominant annual periodicity, displaying the highest amplitude in their respective spectra; in addition, seasonal periodicity (128–256 days) during cold seasons of deweathered SO 2 (Figure 3) is more notable in northern cities, implying that emissions from winter heating represent a significant source of air pollution.…”

Section: Resultsmentioning

confidence: 99%

Differentiating Periodic Drivers of Air Quality Changes: A Two‐Step Decomposition Approach Integrating Machine Learning and Wavelet Analysis

Song,

Wu,

Dai

et al. 2024

JGR Atmospheres

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Air quality time series exhibit significant periodic patterns, which are linked to a diverse array of emission sources and atmospheric processes. To discern and distinguish these periodic drivers, we have devised a two‐step decomposition approach that integrates a machine learning‐based model for weather normalization with Morlet wavelet analysis. This approach was applied to a 7‐year data set encompassing six regulated air pollutants across eight Chinese cities. Our analysis revealed distinct periodicities in weather‐normalized concentrations of primary air pollutants: a dominant annual cycle with periodicity around 365 days, which accounts for over 50% of the variance on average and is primarily driven by recurrent winter heating activities; daily cycles characterized by regular diurnal patterns attributable to combustion sources such as traffic; and periodicities exceeding 512 days that associated with long‐term regulatory policies targeting SO2. Particularly notable was the significant drop in the strength of the annual cycle in northern cities following the implementation of China's clean heating policies in 2017/2018, affirming the success of these initiatives. Additionally, diurnal dispersion and photochemistry, large‐scale atmospheric circulation, and synoptical weather patterns are likely responsible for the observed daily cycle (accounting for over 40% of the variance), annual periodicities, and intra‐monthly variations in the meteorologically driven concentrations, respectively. The varying power of these periodic drivers across time and locations implies the heterogeneity of emission rates and region‐specific climates. This work highlights the efficacy of this decomposition approach in air quality research, warranting attention for its potential value for enhancing our understanding of air pollution dynamics.

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Section: Resultsmentioning

confidence: 99%

Differentiating Periodic Drivers of Air Quality Changes: A Two‐Step Decomposition Approach Integrating Machine Learning and Wavelet Analysis

Song,

Wu,

Dai

et al. 2024

JGR Atmospheres

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“…All pollutants (SO 2 , NO 2 , PM 10 , PM 2.5 , and CO) had a negative correlation with O 3 , especially PM 2.5 . Based on this finding, researchers concluded that a higher concentration of PM 2.5 would inhibit the secondary generation of O 3 [ 30 ]. The continuous emission reduction measures in Anhui significantly decreased the PM 2.5 concentration, but the inhibitory effect on increasing O 3 concentration tended to weaken.…”

Section: Resultsmentioning

confidence: 99%

Spatiotemporal variation and influencing factors of air pollution in Anhui Province

Sun

2023

Heliyon

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“…In this atmospheric condition, it was favorable for surface ozone to be aggravated with the increased NO 2 emission in the dry year. By using the Kolmogorov-Zurbenko filter, Zhang et al [32] concluded meteorological factors only had ~20% of the contribution to the long-term trend components of O 3 in Shenzhen City (in Guangdong province) compared to emission factors. However, in the present study, the influence of climatic anomalies of drought could contribute significantly to ozone variation than is expected in terms of interannual comparisons.…”

Section: The Aggravation Of Surface Ozone In the Dry Yearmentioning

confidence: 99%

Contrasting Near-Surface Ozone Pollution in Wet and Dry Year over China

Ding

Jiang

2023

IJERPH

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The near-surface ozone concentration was evaluated in two typical years with contrasting climatic impacts over the China region induced by El Niño–Southern Oscillation, which had either dry conditions (drought) with intense solar radiation and higher temperatures or wet conditions with opposite meteorological conditions. Surface ozone was observed to aggravate notably by 30% over Northern China in summer and by 50% over Eastern China in autumn in the dry year compared to the wet year. The ozone aggravation was found to be mainly ascribed to the reduced precipitation (relative humidity), enhanced solar radiation and increased temperature rather than primary emission (indicated by carbon monoxide). The health impacts showed the mortality attributable to ozone sharply increased by ~55% in Guangdong while the number of cases dying from ozone-related respiratory diseases per 100,000 population at risk was elevated by ~41% and ~17% for Guangdong (in the Pearl River Delta) and Jiangsu (in the Yangtze River Delta) province (two regions that have been reported to be highly influenced by surface ozone in China), respectively, in the dry year relative to the wet year, indicative of the significant adverse health effects of ozone aggravation. These results highlight the essential contribution of climate anomalies to surface ozone pollution. Efforts to suppress ozone aggravation can be beneficial to public health if extreme drought is predicted, and reasonable policy is implemented.

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Spatiotemporal trends and impact factors of PM<sub>2.5</sub> and O<sub>3</sub> pollution in major cities in China during 2015–2020

Cited by 10 publications

References 67 publications

Differentiating Periodic Drivers of Air Quality Changes: A Two‐Step Decomposition Approach Integrating Machine Learning and Wavelet Analysis

Differentiating Periodic Drivers of Air Quality Changes: A Two‐Step Decomposition Approach Integrating Machine Learning and Wavelet Analysis

Spatiotemporal variation and influencing factors of air pollution in Anhui Province

Contrasting Near-Surface Ozone Pollution in Wet and Dry Year over China

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